venue stringclasses 1
value | title stringlengths 18 162 | abstract stringlengths 252 1.89k | doc_id stringlengths 32 32 | publication_year int64 2.02k 2.02k | sentences listlengths 1 13 | events listlengths 1 24 | document listlengths 50 348 |
|---|---|---|---|---|---|---|---|
ACL | Universal Decompositional Semantic Parsing | We introduce a transductive model for parsing into Universal Decompositional Semantics (UDS) representations, which jointly learns to map natural language utterances into UDS graph structures and annotate the graph with decompositional semantic attribute scores. We also introduce a strong pipeline model for parsing int... | d64ccc914e4f06ce406ec5b6c87f0f0a | 2,020 | [
"we introduce a transductive model for parsing into universal decompositional semantics ( uds ) representations , which jointly learns to map natural language utterances into uds graph structures and annotate the graph with decompositional semantic attribute scores .",
"we also introduce a strong pipeline model f... | [
{
"event_type": "PRP",
"arguments": [
{
"text": "we",
"nugget_type": "OG",
"argument_type": "Proposer",
"tokens": [
"we"
],
"offsets": [
0
]
},
{
"text": "transductive model",
"nugget_type": "APP",
... | [
"we",
"introduce",
"a",
"transductive",
"model",
"for",
"parsing",
"into",
"universal",
"decompositional",
"semantics",
"(",
"uds",
")",
"representations",
",",
"which",
"jointly",
"learns",
"to",
"map",
"natural",
"language",
"utterances",
"into",
"uds",
"graph",... |
ACL | GL-CLeF: A Global–Local Contrastive Learning Framework for Cross-lingual Spoken Language Understanding | Due to high data demands of current methods, attention to zero-shot cross-lingual spoken language understanding (SLU) has grown, as such approaches greatly reduce human annotation effort. However, existing models solely rely on shared parameters, which can only perform implicit alignment across languages. We present Gl... | c341a3f2700ca4e1cce92a250751070e | 2,022 | [
"due to high data demands of current methods , attention to zero - shot cross - lingual spoken language understanding ( slu ) has grown , as such approaches greatly reduce human annotation effort .",
"however , existing models solely rely on shared parameters , which can only perform implicit alignment across lan... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "zero - shot cross - lingual spoken language understanding",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"zero",
"-",
"shot",
"cross",
"-",
"ling... | [
"due",
"to",
"high",
"data",
"demands",
"of",
"current",
"methods",
",",
"attention",
"to",
"zero",
"-",
"shot",
"cross",
"-",
"lingual",
"spoken",
"language",
"understanding",
"(",
"slu",
")",
"has",
"grown",
",",
"as",
"such",
"approaches",
"greatly",
"r... |
ACL | A Survey of Code-switching: Linguistic and Social Perspectives for Language Technologies | The analysis of data in which multiple languages are represented has gained popularity among computational linguists in recent years. So far, much of this research focuses mainly on the improvement of computational methods and largely ignores linguistic and social aspects of C-S discussed across a wide range of languag... | 8b72b3c881b1107d142ac97f6e1b7e02 | 2,021 | [
"the analysis of data in which multiple languages are represented has gained popularity among computational linguists in recent years .",
"so far , much of this research focuses mainly on the improvement of computational methods and largely ignores linguistic and social aspects of c - s discussed across a wide ra... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "analysis of data in which multiple languages",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"analysis",
"of",
"data",
"in",
"which",
"multiple",
... | [
"the",
"analysis",
"of",
"data",
"in",
"which",
"multiple",
"languages",
"are",
"represented",
"has",
"gained",
"popularity",
"among",
"computational",
"linguists",
"in",
"recent",
"years",
".",
"so",
"far",
",",
"much",
"of",
"this",
"research",
"focuses",
"m... |
ACL | AMR Parsing via Graph-Sequence Iterative Inference | We propose a new end-to-end model that treats AMR parsing as a series of dual decisions on the input sequence and the incrementally constructed graph. At each time step, our model performs multiple rounds of attention, reasoning, and composition that aim to answer two critical questions: (1) which part of the input seq... | f96416648b0257fac86c581d5671017a | 2,020 | [
"we propose a new end - to - end model that treats amr parsing as a series of dual decisions on the input sequence and the incrementally constructed graph .",
"at each time step , our model performs multiple rounds of attention , reasoning , and composition that aim to answer two critical questions : ( 1 ) which ... | [
{
"event_type": "PRP",
"arguments": [
{
"text": "we",
"nugget_type": "OG",
"argument_type": "Proposer",
"tokens": [
"we"
],
"offsets": [
0
]
},
{
"text": "end - to - end model",
"nugget_type": "APP"... | [
"we",
"propose",
"a",
"new",
"end",
"-",
"to",
"-",
"end",
"model",
"that",
"treats",
"amr",
"parsing",
"as",
"a",
"series",
"of",
"dual",
"decisions",
"on",
"the",
"input",
"sequence",
"and",
"the",
"incrementally",
"constructed",
"graph",
".",
"at",
"e... |
ACL | IMoJIE: Iterative Memory-Based Joint Open Information Extraction | While traditional systems for Open Information Extraction were statistical and rule-based, recently neural models have been introduced for the task. Our work builds upon CopyAttention, a sequence generation OpenIE model (Cui et. al. 18). Our analysis reveals that CopyAttention produces a constant number of extractions ... | 07579ca58d06f7dcd979bf12008381f7 | 2,020 | [
"while traditional systems for open information extraction were statistical and rule - based , recently neural models have been introduced for the task .",
"our work builds upon copyattention , a sequence generation openie model ( cui et .",
"al . 18 ) .",
"our analysis reveals that copyattention produces a c... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "systems for open information extraction",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"systems",
"for",
"open",
"information",
"extraction"
],
... | [
"while",
"traditional",
"systems",
"for",
"open",
"information",
"extraction",
"were",
"statistical",
"and",
"rule",
"-",
"based",
",",
"recently",
"neural",
"models",
"have",
"been",
"introduced",
"for",
"the",
"task",
".",
"our",
"work",
"builds",
"upon",
"c... |
ACL | mTVR: Multilingual Moment Retrieval in Videos | We introduce mTVR, a large-scale multilingual video moment retrieval dataset, containing 218K English and Chinese queries from 21.8K TV show video clips. The dataset is collected by extending the popular TVR dataset (in English) with paired Chinese queries and subtitles. Compared to existing moment retrieval datasets, ... | ff13166295eb8066b30f6735e1229ce8 | 2,021 | [
"we introduce mtvr , a large - scale multilingual video moment retrieval dataset , containing 218k english and chinese queries from 21 . 8k tv show video clips .",
"the dataset is collected by extending the popular tvr dataset ( in english ) with paired chinese queries and subtitles .",
"compared to existing mo... | [
{
"event_type": "PRP",
"arguments": [
{
"text": "we",
"nugget_type": "OG",
"argument_type": "Proposer",
"tokens": [
"we"
],
"offsets": [
0
]
},
{
"text": "multilingual video moment retrieval dataset",
... | [
"we",
"introduce",
"mtvr",
",",
"a",
"large",
"-",
"scale",
"multilingual",
"video",
"moment",
"retrieval",
"dataset",
",",
"containing",
"218k",
"english",
"and",
"chinese",
"queries",
"from",
"21",
".",
"8k",
"tv",
"show",
"video",
"clips",
".",
"the",
"... |
ACL | iSarcasm: A Dataset of Intended Sarcasm | We consider the distinction between intended and perceived sarcasm in the context of textual sarcasm detection. The former occurs when an utterance is sarcastic from the perspective of its author, while the latter occurs when the utterance is interpreted as sarcastic by the audience. We show the limitations of previous... | b5def98efa42286652a857948a6598be | 2,020 | [
"we consider the distinction between intended and perceived sarcasm in the context of textual sarcasm detection .",
"the former occurs when an utterance is sarcastic from the perspective of its author , while the latter occurs when the utterance is interpreted as sarcastic by the audience .",
"we show the limit... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "textual sarcasm detection",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"textual",
"sarcasm",
"detection"
],
"offsets": [
13,
14,
... | [
"we",
"consider",
"the",
"distinction",
"between",
"intended",
"and",
"perceived",
"sarcasm",
"in",
"the",
"context",
"of",
"textual",
"sarcasm",
"detection",
".",
"the",
"former",
"occurs",
"when",
"an",
"utterance",
"is",
"sarcastic",
"from",
"the",
"perspecti... |
ACL | Alignment Rationale for Natural Language Inference | Deep learning models have achieved great success on the task of Natural Language Inference (NLI), though only a few attempts try to explain their behaviors. Existing explanation methods usually pick prominent features such as words or phrases from the input text. However, for NLI, alignments among words or phrases are ... | c140ec51539c0d2f2e15be0eef20636c | 2,021 | [
"deep learning models have achieved great success on the task of natural language inference ( nli ) , though only a few attempts try to explain their behaviors .",
"existing explanation methods usually pick prominent features such as words or phrases from the input text .",
"however , for nli , alignments among... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "deep learning models",
"nugget_type": "APP",
"argument_type": "Target",
"tokens": [
"deep",
"learning",
"models"
],
"offsets": [
0,
1,
2
... | [
"deep",
"learning",
"models",
"have",
"achieved",
"great",
"success",
"on",
"the",
"task",
"of",
"natural",
"language",
"inference",
"(",
"nli",
")",
",",
"though",
"only",
"a",
"few",
"attempts",
"try",
"to",
"explain",
"their",
"behaviors",
".",
"existing"... |
ACL | Single-/Multi-Source Cross-Lingual NER via Teacher-Student Learning on Unlabeled Data in Target Language | To better tackle the named entity recognition (NER) problem on languages with little/no labeled data, cross-lingual NER must effectively leverage knowledge learned from source languages with rich labeled data. Previous works on cross-lingual NER are mostly based on label projection with pairwise texts or direct model t... | 0a8abc765e42d12dd643b0733aaca445 | 2,020 | [
"to better tackle the named entity recognition ( ner ) problem on languages with little / no labeled data , cross - lingual ner must effectively leverage knowledge learned from source languages with rich labeled data .",
"previous works on cross - lingual ner are mostly based on label projection with pairwise tex... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "cross - lingual ner",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"cross",
"-",
"lingual",
"ner"
],
"offsets": [
20,
21,
... | [
"to",
"better",
"tackle",
"the",
"named",
"entity",
"recognition",
"(",
"ner",
")",
"problem",
"on",
"languages",
"with",
"little",
"/",
"no",
"labeled",
"data",
",",
"cross",
"-",
"lingual",
"ner",
"must",
"effectively",
"leverage",
"knowledge",
"learned",
... |
ACL | Common Sense Beyond English: Evaluating and Improving Multilingual Language Models for Commonsense Reasoning | Commonsense reasoning research has so far been limited to English. We aim to evaluate and improve popular multilingual language models (ML-LMs) to help advance commonsense reasoning (CSR) beyond English. We collect the Mickey corpus, consisting of 561k sentences in 11 different languages, which can be used for analyzin... | b5fe0e31c40e15b74674caa1bb19be12 | 2,021 | [
"commonsense reasoning research has so far been limited to english .",
"we aim to evaluate and improve popular multilingual language models ( ml - lms ) to help advance commonsense reasoning ( csr ) beyond english .",
"we collect the mickey corpus , consisting of 561k sentences in 11 different languages , which... | [
{
"event_type": "WKS",
"arguments": [
{
"text": "we",
"nugget_type": "OG",
"argument_type": "Researcher",
"tokens": [
"we"
],
"offsets": [
11
]
},
{
"text": "popular ml - lms",
"nugget_type": "APP",... | [
"commonsense",
"reasoning",
"research",
"has",
"so",
"far",
"been",
"limited",
"to",
"english",
".",
"we",
"aim",
"to",
"evaluate",
"and",
"improve",
"popular",
"multilingual",
"language",
"models",
"(",
"ml",
"-",
"lms",
")",
"to",
"help",
"advance",
"commo... |
ACL | A Reinforced Generation of Adversarial Examples for Neural Machine Translation | Neural machine translation systems tend to fail on less decent inputs despite its significant efficacy, which may significantly harm the credibility of these systems—fathoming how and when neural-based systems fail in such cases is critical for industrial maintenance. Instead of collecting and analyzing bad cases using... | d34b3fa5e293f36974021391758f6f93 | 2,020 | [
"neural machine translation systems tend to fail on less decent inputs despite its significant efficacy , which may significantly harm the credibility of these systems — fathoming how and when neural - based systems fail in such cases is critical for industrial maintenance .",
"instead of collecting and analyzing... | [
{
"event_type": "RWF",
"arguments": [
{
"text": "neural machine translation systems",
"nugget_type": "APP",
"argument_type": "Concern",
"tokens": [
"neural",
"machine",
"translation",
"systems"
],
"offsets": [
... | [
"neural",
"machine",
"translation",
"systems",
"tend",
"to",
"fail",
"on",
"less",
"decent",
"inputs",
"despite",
"its",
"significant",
"efficacy",
",",
"which",
"may",
"significantly",
"harm",
"the",
"credibility",
"of",
"these",
"systems",
"—",
"fathoming",
"h... |
ACL | Selective Question Answering under Domain Shift | To avoid giving wrong answers, question answering (QA) models need to know when to abstain from answering. Moreover, users often ask questions that diverge from the model’s training data, making errors more likely and thus abstention more critical. In this work, we propose the setting of selective question answering un... | a12b6a99317ff216b49e8413b365119b | 2,020 | [
"to avoid giving wrong answers , question answering ( qa ) models need to know when to abstain from answering .",
"moreover , users often ask questions that diverge from the model ’ s training data , making errors more likely and thus abstention more critical .",
"in this work , we propose the setting of select... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "question answering models",
"nugget_type": "APP",
"argument_type": "Target",
"tokens": [
"question",
"answering",
"models"
],
"offsets": [
6,
7,
... | [
"to",
"avoid",
"giving",
"wrong",
"answers",
",",
"question",
"answering",
"(",
"qa",
")",
"models",
"need",
"to",
"know",
"when",
"to",
"abstain",
"from",
"answering",
".",
"moreover",
",",
"users",
"often",
"ask",
"questions",
"that",
"diverge",
"from",
... |
ACL | Domain Adaptive Dialog Generation via Meta Learning | Domain adaptation is an essential task in dialog system building because there are so many new dialog tasks created for different needs every day. Collecting and annotating training data for these new tasks is costly since it involves real user interactions. We propose a domain adaptive dialog generation method based o... | f7423ab0231b70f3aa051c7fc1eb3c71 | 2,019 | [
"domain adaptation is an essential task in dialog system building because there are so many new dialog tasks created for different needs every day .",
"collecting and annotating training data for these new tasks is costly since it involves real user interactions .",
"we propose a domain adaptive dialog generati... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "domain adaptation",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"domain",
"adaptation"
],
"offsets": [
0,
1
]
}
],
"trigger": ... | [
"domain",
"adaptation",
"is",
"an",
"essential",
"task",
"in",
"dialog",
"system",
"building",
"because",
"there",
"are",
"so",
"many",
"new",
"dialog",
"tasks",
"created",
"for",
"different",
"needs",
"every",
"day",
".",
"collecting",
"and",
"annotating",
"t... |
ACL | CICERO: A Dataset for Contextualized Commonsense Inference in Dialogues | This paper addresses the problem of dialogue reasoning with contextualized commonsense inference. We curate CICERO, a dataset of dyadic conversations with five types of utterance-level reasoning-based inferences: cause, subsequent event, prerequisite, motivation, and emotional reaction. The dataset contains 53,105 of s... | 4838b82354ef2da271e9085fb2956597 | 2,022 | [
"this paper addresses the problem of dialogue reasoning with contextualized commonsense inference .",
"we curate cicero , a dataset of dyadic conversations with five types of utterance - level reasoning - based inferences : cause , subsequent event , prerequisite , motivation , and emotional reaction .",
"the d... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "dialogue reasoning with contextualized commonsense inference",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"dialogue",
"reasoning",
"with",
"contextualized",
... | [
"this",
"paper",
"addresses",
"the",
"problem",
"of",
"dialogue",
"reasoning",
"with",
"contextualized",
"commonsense",
"inference",
".",
"we",
"curate",
"cicero",
",",
"a",
"dataset",
"of",
"dyadic",
"conversations",
"with",
"five",
"types",
"of",
"utterance",
... |
ACL | Global Textual Relation Embedding for Relational Understanding | Pre-trained embeddings such as word embeddings and sentence embeddings are fundamental tools facilitating a wide range of downstream NLP tasks. In this work, we investigate how to learn a general-purpose embedding of textual relations, defined as the shortest dependency path between entities. Textual relation embedding... | f2c9dccb266fd9273368252850d646d8 | 2,019 | [
"pre - trained embeddings such as word embeddings and sentence embeddings are fundamental tools facilitating a wide range of downstream nlp tasks .",
"in this work , we investigate how to learn a general - purpose embedding of textual relations , defined as the shortest dependency path between entities .",
"tex... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "nlp tasks",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"nlp",
"tasks"
],
"offsets": [
20,
21
]
}
],
"trigger": {
"text"... | [
"pre",
"-",
"trained",
"embeddings",
"such",
"as",
"word",
"embeddings",
"and",
"sentence",
"embeddings",
"are",
"fundamental",
"tools",
"facilitating",
"a",
"wide",
"range",
"of",
"downstream",
"nlp",
"tasks",
".",
"in",
"this",
"work",
",",
"we",
"investigat... |
ACL | Adjusting the Precision-Recall Trade-Off with Align-and-Predict Decoding for Grammatical Error Correction | Modern writing assistance applications are always equipped with a Grammatical Error Correction (GEC) model to correct errors in user-entered sentences. Different scenarios have varying requirements for correction behavior, e.g., performing more precise corrections (high precision) or providing more candidates for users... | 1665b60a190a8823b599f5c5a767bd64 | 2,022 | [
"modern writing assistance applications are always equipped with a grammatical error correction ( gec ) model to correct errors in user - entered sentences .",
"different scenarios have varying requirements for correction behavior , e . g . , performing more precise corrections ( high precision ) or providing mor... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "modern writing assistance applications",
"nugget_type": "APP",
"argument_type": "Target",
"tokens": [
"modern",
"writing",
"assistance",
"applications"
],
"offsets":... | [
"modern",
"writing",
"assistance",
"applications",
"are",
"always",
"equipped",
"with",
"a",
"grammatical",
"error",
"correction",
"(",
"gec",
")",
"model",
"to",
"correct",
"errors",
"in",
"user",
"-",
"entered",
"sentences",
".",
"different",
"scenarios",
"hav... |
ACL | Multi-hop Reading Comprehension through Question Decomposition and Rescoring | Multi-hop Reading Comprehension (RC) requires reasoning and aggregation across several paragraphs. We propose a system for multi-hop RC that decomposes a compositional question into simpler sub-questions that can be answered by off-the-shelf single-hop RC models. Since annotations for such decomposition are expensive, ... | e5e2c0e14c1408b28f6f932334efb932 | 2,019 | [
"multi - hop reading comprehension ( rc ) requires reasoning and aggregation across several paragraphs .",
"we propose a system for multi - hop rc that decomposes a compositional question into simpler sub - questions that can be answered by off - the - shelf single - hop rc models .",
"since annotations for suc... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "multi - hop reading comprehension",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"multi",
"-",
"hop",
"reading",
"comprehension"
],
"offset... | [
"multi",
"-",
"hop",
"reading",
"comprehension",
"(",
"rc",
")",
"requires",
"reasoning",
"and",
"aggregation",
"across",
"several",
"paragraphs",
".",
"we",
"propose",
"a",
"system",
"for",
"multi",
"-",
"hop",
"rc",
"that",
"decomposes",
"a",
"compositional"... |
ACL | Cross-modal Language Generation using Pivot Stabilization for Web-scale Language Coverage | Cross-modal language generation tasks such as image captioning are directly hurt in their ability to support non-English languages by the trend of data-hungry models combined with the lack of non-English annotations. We investigate potential solutions for combining existing language-generation annotations in English wi... | 41844aa1e09be0591eda638bbb402b15 | 2,020 | [
"cross - modal language generation tasks such as image captioning are directly hurt in their ability to support non - english languages by the trend of data - hungry models combined with the lack of non - english annotations .",
"we investigate potential solutions for combining existing language - generation anno... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "cross - modal language generation tasks",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"cross",
"-",
"modal",
"language",
"generation",
"tasks"
... | [
"cross",
"-",
"modal",
"language",
"generation",
"tasks",
"such",
"as",
"image",
"captioning",
"are",
"directly",
"hurt",
"in",
"their",
"ability",
"to",
"support",
"non",
"-",
"english",
"languages",
"by",
"the",
"trend",
"of",
"data",
"-",
"hungry",
"model... |
ACL | A unified approach to sentence segmentation of punctuated text in many languages | The sentence is a fundamental unit of text processing. Yet sentences in the wild are commonly encountered not in isolation, but unsegmented within larger paragraphs and documents. Therefore, the first step in many NLP pipelines is sentence segmentation. Despite its importance, this step is the subject of relatively lit... | b6e47e0ab8f231753d3f752bc287d5f6 | 2,021 | [
"the sentence is a fundamental unit of text processing .",
"yet sentences in the wild are commonly encountered not in isolation , but unsegmented within larger paragraphs and documents .",
"therefore , the first step in many nlp pipelines is sentence segmentation .",
"despite its importance , this step is the... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "sentence segmentation",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"sentence",
"segmentation"
],
"offsets": [
40,
41
]
}
],
"... | [
"the",
"sentence",
"is",
"a",
"fundamental",
"unit",
"of",
"text",
"processing",
".",
"yet",
"sentences",
"in",
"the",
"wild",
"are",
"commonly",
"encountered",
"not",
"in",
"isolation",
",",
"but",
"unsegmented",
"within",
"larger",
"paragraphs",
"and",
"docu... |
ACL | New Intent Discovery with Pre-training and Contrastive Learning | New intent discovery aims to uncover novel intent categories from user utterances to expand the set of supported intent classes. It is a critical task for the development and service expansion of a practical dialogue system. Despite its importance, this problem remains under-explored in the literature. Existing approac... | 3a1b72322a7b1460c636945d1d260a22 | 2,022 | [
"new intent discovery aims to uncover novel intent categories from user utterances to expand the set of supported intent classes .",
"it is a critical task for the development and service expansion of a practical dialogue system .",
"despite its importance , this problem remains under - explored in the literatu... | [
{
"event_type": "ITT",
"arguments": [],
"trigger": {
"text": "uncover",
"tokens": [
"uncover"
],
"offsets": [
5
]
}
},
{
"event_type": "RWF",
"arguments": [
{
"text": "existing approaches",
"nugget_type": "APP",
... | [
"new",
"intent",
"discovery",
"aims",
"to",
"uncover",
"novel",
"intent",
"categories",
"from",
"user",
"utterances",
"to",
"expand",
"the",
"set",
"of",
"supported",
"intent",
"classes",
".",
"it",
"is",
"a",
"critical",
"task",
"for",
"the",
"development",
... |
ACL | A Sweet Rabbit Hole by DARCY: Using Honeypots to Detect Universal Trigger’s Adversarial Attacks | The Universal Trigger (UniTrigger) is a recently-proposed powerful adversarial textual attack method. Utilizing a learning-based mechanism, UniTrigger generates a fixed phrase that, when added to any benign inputs, can drop the prediction accuracy of a textual neural network (NN) model to near zero on a target class. T... | d708af5bf44c3ba54067f1d55df0092c | 2,021 | [
"the universal trigger ( unitrigger ) is a recently - proposed powerful adversarial textual attack method .",
"utilizing a learning - based mechanism , unitrigger generates a fixed phrase that , when added to any benign inputs , can drop the prediction accuracy of a textual neural network ( nn ) model to near zer... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "universal trigger",
"nugget_type": "APP",
"argument_type": "Target",
"tokens": [
"universal",
"trigger"
],
"offsets": [
1,
2
]
}
],
"trigger": ... | [
"the",
"universal",
"trigger",
"(",
"unitrigger",
")",
"is",
"a",
"recently",
"-",
"proposed",
"powerful",
"adversarial",
"textual",
"attack",
"method",
".",
"utilizing",
"a",
"learning",
"-",
"based",
"mechanism",
",",
"unitrigger",
"generates",
"a",
"fixed",
... |
ACL | PriMock57: A Dataset Of Primary Care Mock Consultations | Recent advances in Automatic Speech Recognition (ASR) have made it possible to reliably produce automatic transcripts of clinician-patient conversations. However, access to clinical datasets is heavily restricted due to patient privacy, thus slowing down normal research practices. We detail the development of a public ... | 3f6f04d83615261a704c5035bd224057 | 2,022 | [
"recent advances in automatic speech recognition ( asr ) have made it possible to reliably produce automatic transcripts of clinician - patient conversations .",
"however , access to clinical datasets is heavily restricted due to patient privacy , thus slowing down normal research practices .",
"we detail the d... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "automatic speech recognition",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"automatic",
"speech",
"recognition"
],
"offsets": [
3,
4,
... | [
"recent",
"advances",
"in",
"automatic",
"speech",
"recognition",
"(",
"asr",
")",
"have",
"made",
"it",
"possible",
"to",
"reliably",
"produce",
"automatic",
"transcripts",
"of",
"clinician",
"-",
"patient",
"conversations",
".",
"however",
",",
"access",
"to",... |
ACL | Bridging by Word: Image Grounded Vocabulary Construction for Visual Captioning | Image Captioning aims at generating a short description for an image. Existing research usually employs the architecture of CNN-RNN that views the generation as a sequential decision-making process and the entire dataset vocabulary is used as decoding space. They suffer from generating high frequent n-gram with irrelev... | 60b1316c4a4c989ab0ebba07738632f5 | 2,019 | [
"image captioning aims at generating a short description for an image .",
"existing research usually employs the architecture of cnn - rnn that views the generation as a sequential decision - making process and the entire dataset vocabulary is used as decoding space .",
"they suffer from generating high frequen... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "image captioning",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"image",
"captioning"
],
"offsets": [
0,
1
]
}
],
"trigger": {
... | [
"image",
"captioning",
"aims",
"at",
"generating",
"a",
"short",
"description",
"for",
"an",
"image",
".",
"existing",
"research",
"usually",
"employs",
"the",
"architecture",
"of",
"cnn",
"-",
"rnn",
"that",
"views",
"the",
"generation",
"as",
"a",
"sequentia... |
ACL | Scheduled Multi-task Learning for Neural Chat Translation | Neural Chat Translation (NCT) aims to translate conversational text into different languages. Existing methods mainly focus on modeling the bilingual dialogue characteristics (e.g., coherence) to improve chat translation via multi-task learning on small-scale chat translation data. Although the NCT models have achieved... | 9f29010944bd19ab9a3843e8429d1dd2 | 2,022 | [
"neural chat translation ( nct ) aims to translate conversational text into different languages .",
"existing methods mainly focus on modeling the bilingual dialogue characteristics ( e . g . , coherence ) to improve chat translation via multi - task learning on small - scale chat translation data .",
"although... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "nct",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"nct"
],
"offsets": [
52
]
}
],
"trigger": {
"text": "translate",
"tokens": [
... | [
"neural",
"chat",
"translation",
"(",
"nct",
")",
"aims",
"to",
"translate",
"conversational",
"text",
"into",
"different",
"languages",
".",
"existing",
"methods",
"mainly",
"focus",
"on",
"modeling",
"the",
"bilingual",
"dialogue",
"characteristics",
"(",
"e",
... |
ACL | SCD: Self-Contrastive Decorrelation of Sentence Embeddings | In this paper, we propose Self-Contrastive Decorrelation (SCD), a self-supervised approach. Given an input sentence, it optimizes a joint self-contrastive and decorrelation objective. Learning a representation is facilitated by leveraging the contrast arising from the instantiation of standard dropout at different rate... | 5f4e1f8dbad2c26a839cd810657ec134 | 2,022 | [
"in this paper , we propose self - contrastive decorrelation ( scd ) , a self - supervised approach .",
"given an input sentence , it optimizes a joint self - contrastive and decorrelation objective .",
"learning a representation is facilitated by leveraging the contrast arising from the instantiation of standa... | [
{
"event_type": "PRP",
"arguments": [
{
"text": "we",
"nugget_type": "OG",
"argument_type": "Proposer",
"tokens": [
"we"
],
"offsets": [
4
]
},
{
"text": "self - contrastive decorrelation",
"nugget_... | [
"in",
"this",
"paper",
",",
"we",
"propose",
"self",
"-",
"contrastive",
"decorrelation",
"(",
"scd",
")",
",",
"a",
"self",
"-",
"supervised",
"approach",
".",
"given",
"an",
"input",
"sentence",
",",
"it",
"optimizes",
"a",
"joint",
"self",
"-",
"contr... |
ACL | Making Fast Graph-based Algorithms with Graph Metric Embeddings | Graph measures, such as node distances, are inefficient to compute. We explore dense vector representations as an effective way to approximate the same information. We introduce a simple yet efficient and effective approach for learning graph embeddings. Instead of directly operating on the graph structure, our method ... | 13f091d4a86234f1b06ee01779da0b8c | 2,019 | [
"graph measures , such as node distances , are inefficient to compute .",
"we explore dense vector representations as an effective way to approximate the same information .",
"we introduce a simple yet efficient and effective approach for learning graph embeddings .",
"instead of directly operating on the gra... | [
{
"event_type": "WKS",
"arguments": [
{
"text": "we",
"nugget_type": "OG",
"argument_type": "Researcher",
"tokens": [
"we"
],
"offsets": [
13
]
},
{
"text": "approximate",
"nugget_type": "E-PUR",
... | [
"graph",
"measures",
",",
"such",
"as",
"node",
"distances",
",",
"are",
"inefficient",
"to",
"compute",
".",
"we",
"explore",
"dense",
"vector",
"representations",
"as",
"an",
"effective",
"way",
"to",
"approximate",
"the",
"same",
"information",
".",
"we",
... |
ACL | Hybrid Semantics for Goal-Directed Natural Language Generation | We consider the problem of generating natural language given a communicative goal and a world description. We ask the question: is it possible to combine complementary meaning representations to scale a goal-directed NLG system without losing expressiveness? In particular, we consider using two meaning representations,... | 43e30256e6e56275e0d211bd2967c812 | 2,022 | [
"we consider the problem of generating natural language given a communicative goal and a world description .",
"we ask the question : is it possible to combine complementary meaning representations to scale a goal - directed nlg system without losing expressiveness ?",
"in particular , we consider using two mea... | [
{
"event_type": "PUR",
"arguments": [
{
"text": "sentence generation",
"nugget_type": "TAK",
"argument_type": "Aim",
"tokens": [
"sentence",
"generation"
],
"offsets": [
82,
83
]
}
],
"trigger... | [
"we",
"consider",
"the",
"problem",
"of",
"generating",
"natural",
"language",
"given",
"a",
"communicative",
"goal",
"and",
"a",
"world",
"description",
".",
"we",
"ask",
"the",
"question",
":",
"is",
"it",
"possible",
"to",
"combine",
"complementary",
"meani... |
ACL | Focus on the Target’s Vocabulary: Masked Label Smoothing for Machine Translation | Label smoothing and vocabulary sharing are two widely used techniques in neural machine translation models. However, we argue that simply applying both techniques can be conflicting and even leads to sub-optimal performance. When allocating smoothed probability, original label smoothing treats the source-side words tha... | 15f34108300a0576d372ae5f42efc30d | 2,022 | [
"label smoothing and vocabulary sharing are two widely used techniques in neural machine translation models .",
"however , we argue that simply applying both techniques can be conflicting and even leads to sub - optimal performance .",
"when allocating smoothed probability , original label smoothing treats the ... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "label smoothing",
"nugget_type": "APP",
"argument_type": "Target",
"tokens": [
"label",
"smoothing"
],
"offsets": [
0,
1
]
},
{
"text": "... | [
"label",
"smoothing",
"and",
"vocabulary",
"sharing",
"are",
"two",
"widely",
"used",
"techniques",
"in",
"neural",
"machine",
"translation",
"models",
".",
"however",
",",
"we",
"argue",
"that",
"simply",
"applying",
"both",
"techniques",
"can",
"be",
"conflict... |
ACL | Generation-Augmented Retrieval for Open-Domain Question Answering | We propose Generation-Augmented Retrieval (GAR) for answering open-domain questions, which augments a query through text generation of heuristically discovered relevant contexts without external resources as supervision. We demonstrate that the generated contexts substantially enrich the semantics of the queries and GA... | 73b1b56effdf9bf61280ca4bdb0c0b29 | 2,021 | [
"we propose generation - augmented retrieval ( gar ) for answering open - domain questions , which augments a query through text generation of heuristically discovered relevant contexts without external resources as supervision .",
"we demonstrate that the generated contexts substantially enrich the semantics of ... | [
{
"event_type": "PRP",
"arguments": [
{
"text": "we",
"nugget_type": "OG",
"argument_type": "Proposer",
"tokens": [
"we"
],
"offsets": [
0
]
},
{
"text": "generation - augmented retrieval",
"nugget_... | [
"we",
"propose",
"generation",
"-",
"augmented",
"retrieval",
"(",
"gar",
")",
"for",
"answering",
"open",
"-",
"domain",
"questions",
",",
"which",
"augments",
"a",
"query",
"through",
"text",
"generation",
"of",
"heuristically",
"discovered",
"relevant",
"cont... |
ACL | PlotCoder: Hierarchical Decoding for Synthesizing Visualization Code in Programmatic Context | Creating effective visualization is an important part of data analytics. While there are many libraries for creating visualization, writing such code remains difficult given the myriad of parameters that users need to provide. In this paper, we propose the new task of synthesizing visualization programs from a combinat... | 0ab9be8c1e777069aad37feb3b065581 | 2,021 | [
"creating effective visualization is an important part of data analytics .",
"while there are many libraries for creating visualization , writing such code remains difficult given the myriad of parameters that users need to provide .",
"in this paper , we propose the new task of synthesizing visualization progr... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "creating effective visualization",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"creating",
"effective",
"visualization"
],
"offsets": [
0,
... | [
"creating",
"effective",
"visualization",
"is",
"an",
"important",
"part",
"of",
"data",
"analytics",
".",
"while",
"there",
"are",
"many",
"libraries",
"for",
"creating",
"visualization",
",",
"writing",
"such",
"code",
"remains",
"difficult",
"given",
"the",
"... |
ACL | Reinforced Dynamic Reasoning for Conversational Question Generation | This paper investigates a new task named Conversational Question Generation (CQG) which is to generate a question based on a passage and a conversation history (i.e., previous turns of question-answer pairs). CQG is a crucial task for developing intelligent agents that can drive question-answering style conversations o... | 0befbae084b1a0f9004461ca4d558226 | 2,019 | [
"this paper investigates a new task named conversational question generation ( cqg ) which is to generate a question based on a passage and a conversation history ( i . e . , previous turns of question - answer pairs ) .",
"cqg is a crucial task for developing intelligent agents that can drive question - answerin... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "conversational question generation",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"conversational",
"question",
"generation"
],
"offsets": [
7,
... | [
"this",
"paper",
"investigates",
"a",
"new",
"task",
"named",
"conversational",
"question",
"generation",
"(",
"cqg",
")",
"which",
"is",
"to",
"generate",
"a",
"question",
"based",
"on",
"a",
"passage",
"and",
"a",
"conversation",
"history",
"(",
"i",
".",
... |
ACL | Hypergraph Transformer: Weakly-Supervised Multi-hop Reasoning for Knowledge-based Visual Question Answering | Knowledge-based visual question answering (QA) aims to answer a question which requires visually-grounded external knowledge beyond image content itself. Answering complex questions that require multi-hop reasoning under weak supervision is considered as a challenging problem since i) no supervision is given to the rea... | 1e14f72ab532f63f9c64e18512798563 | 2,022 | [
"knowledge - based visual question answering ( qa ) aims to answer a question which requires visually - grounded external knowledge beyond image content itself .",
"answering complex questions that require multi - hop reasoning under weak supervision is considered as a challenging problem since i )",
"no superv... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "knowledge - based visual qa",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"knowledge",
"-",
"based",
"visual",
"qa"
],
"offsets": [
... | [
"knowledge",
"-",
"based",
"visual",
"question",
"answering",
"(",
"qa",
")",
"aims",
"to",
"answer",
"a",
"question",
"which",
"requires",
"visually",
"-",
"grounded",
"external",
"knowledge",
"beyond",
"image",
"content",
"itself",
".",
"answering",
"complex",... |
ACL | Hierarchical Transformers for Multi-Document Summarization | In this paper, we develop a neural summarization model which can effectively process multiple input documents and distill Transformer architecture with the ability to encode documents in a hierarchical manner. We represent cross-document relationships via an attention mechanism which allows to share information as oppo... | c92f50cc2afd4aff4d7bf3f5a7a2515a | 2,019 | [
"in this paper , we develop a neural summarization model which can effectively process multiple input documents and distill transformer architecture with the ability to encode documents in a hierarchical manner .",
"we represent cross - document relationships via an attention mechanism which allows to share infor... | [
{
"event_type": "PRP",
"arguments": [
{
"text": "we",
"nugget_type": "OG",
"argument_type": "Proposer",
"tokens": [
"we"
],
"offsets": [
4
]
},
{
"text": "neural summarization model",
"nugget_type":... | [
"in",
"this",
"paper",
",",
"we",
"develop",
"a",
"neural",
"summarization",
"model",
"which",
"can",
"effectively",
"process",
"multiple",
"input",
"documents",
"and",
"distill",
"transformer",
"architecture",
"with",
"the",
"ability",
"to",
"encode",
"documents"... |
ACL | Hate Speech Detection Based on Sentiment Knowledge Sharing | The wanton spread of hate speech on the internet brings great harm to society and families. It is urgent to establish and improve automatic detection and active avoidance mechanisms for hate speech. While there exist methods for hate speech detection, they stereotype words and hence suffer from inherently biased traini... | 24fbb69f6c4689d07c219adb5588778d | 2,021 | [
"the wanton spread of hate speech on the internet brings great harm to society and families .",
"it is urgent to establish and improve automatic detection and active avoidance mechanisms for hate speech .",
"while there exist methods for hate speech detection , they stereotype words and hence suffer from inhere... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "hate speech",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"hate",
"speech"
],
"offsets": [
4,
5
]
}
],
"trigger": {
"tex... | [
"the",
"wanton",
"spread",
"of",
"hate",
"speech",
"on",
"the",
"internet",
"brings",
"great",
"harm",
"to",
"society",
"and",
"families",
".",
"it",
"is",
"urgent",
"to",
"establish",
"and",
"improve",
"automatic",
"detection",
"and",
"active",
"avoidance",
... |
ACL | Towards Comprehensive Patent Approval Predictions:Beyond Traditional Document Classification | Predicting the approval chance of a patent application is a challenging problem involving multiple facets. The most crucial facet is arguably the novelty — 35 U.S. Code § 102 rejects more recent applications that have very similar prior arts. Such novelty evaluations differ the patent approval prediction from conventio... | 9dcb98b527fc6b315fa16082e38d06d6 | 2,022 | [
"predicting the approval chance of a patent application is a challenging problem involving multiple facets .",
"the most crucial facet is arguably the novelty — 35 u . s . code § 102 rejects more recent applications that have very similar prior arts .",
"such novelty evaluations differ the patent approval predi... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "patent application",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"patent",
"application"
],
"offsets": [
6,
7
]
}
],
"trigger"... | [
"predicting",
"the",
"approval",
"chance",
"of",
"a",
"patent",
"application",
"is",
"a",
"challenging",
"problem",
"involving",
"multiple",
"facets",
".",
"the",
"most",
"crucial",
"facet",
"is",
"arguably",
"the",
"novelty",
"—",
"35",
"u",
".",
"s",
".",
... |
ACL | Modeling Morphological Typology for Unsupervised Learning of Language Morphology | This paper describes a language-independent model for fully unsupervised morphological analysis that exploits a universal framework leveraging morphological typology. By modeling morphological processes including suffixation, prefixation, infixation, and full and partial reduplication with constrained stem change rules... | f5f229a90b62ee45f7f5529663c34977 | 2,020 | [
"this paper describes a language - independent model for fully unsupervised morphological analysis that exploits a universal framework leveraging morphological typology .",
"by modeling morphological processes including suffixation , prefixation , infixation , and full and partial reduplication with constrained s... | [
{
"event_type": "WKS",
"arguments": [
{
"text": "language - independent model",
"nugget_type": "APP",
"argument_type": "Content",
"tokens": [
"language",
"-",
"independent",
"model"
],
"offsets": [
4,
... | [
"this",
"paper",
"describes",
"a",
"language",
"-",
"independent",
"model",
"for",
"fully",
"unsupervised",
"morphological",
"analysis",
"that",
"exploits",
"a",
"universal",
"framework",
"leveraging",
"morphological",
"typology",
".",
"by",
"modeling",
"morphological... |
ACL | Reranking for Neural Semantic Parsing | Semantic parsing considers the task of transducing natural language (NL) utterances into machine executable meaning representations (MRs). While neural network-based semantic parsers have achieved impressive improvements over previous methods, results are still far from perfect, and cursory manual inspection can easily... | c58a5ebd661895bcf5dbe21e19df7a2f | 2,019 | [
"semantic parsing considers the task of transducing natural language ( nl ) utterances into machine executable meaning representations ( mrs ) .",
"while neural network - based semantic parsers have achieved impressive improvements over previous methods , results are still far from perfect , and cursory manual in... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "semantic parsing",
"nugget_type": "APP",
"argument_type": "Target",
"tokens": [
"semantic",
"parsing"
],
"offsets": [
0,
1
]
}
],
"trigger": {
... | [
"semantic",
"parsing",
"considers",
"the",
"task",
"of",
"transducing",
"natural",
"language",
"(",
"nl",
")",
"utterances",
"into",
"machine",
"executable",
"meaning",
"representations",
"(",
"mrs",
")",
".",
"while",
"neural",
"network",
"-",
"based",
"semanti... |
ACL | It is AI’s Turn to Ask Humans a Question: Question-Answer Pair Generation for Children’s Story Books | Existing question answering (QA) techniques are created mainly to answer questions asked by humans. But in educational applications, teachers often need to decide what questions they should ask, in order to help students to improve their narrative understanding capabilities. We design an automated question-answer gener... | 42ba153a336150f172d7aea84a869dc2 | 2,022 | [
"existing question answering ( qa ) techniques are created mainly to answer questions asked by humans .",
"but in educational applications , teachers often need to decide what questions they should ask , in order to help students to improve their narrative understanding capabilities .",
"we design an automated ... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "question answering",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"question",
"answering"
],
"offsets": [
1,
2
]
}
],
"trigger"... | [
"existing",
"question",
"answering",
"(",
"qa",
")",
"techniques",
"are",
"created",
"mainly",
"to",
"answer",
"questions",
"asked",
"by",
"humans",
".",
"but",
"in",
"educational",
"applications",
",",
"teachers",
"often",
"need",
"to",
"decide",
"what",
"que... |
ACL | Neural-Symbolic Commonsense Reasoner with Relation Predictors | Commonsense reasoning aims to incorporate sets of commonsense facts, retrieved from Commonsense Knowledge Graphs (CKG), to draw conclusion about ordinary situations. The dynamic nature of commonsense knowledge postulates models capable of performing multi-hop reasoning over new situations. This feature also results in ... | 689a0ee6c03152e18dfd1ee60ffafefd | 2,021 | [
"commonsense reasoning aims to incorporate sets of commonsense facts , retrieved from commonsense knowledge graphs ( ckg ) , to draw conclusion about ordinary situations .",
"the dynamic nature of commonsense knowledge postulates models capable of performing multi - hop reasoning over new situations .",
"this f... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "commonsense reasoning",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"commonsense",
"reasoning"
],
"offsets": [
0,
1
]
}
],
"tr... | [
"commonsense",
"reasoning",
"aims",
"to",
"incorporate",
"sets",
"of",
"commonsense",
"facts",
",",
"retrieved",
"from",
"commonsense",
"knowledge",
"graphs",
"(",
"ckg",
")",
",",
"to",
"draw",
"conclusion",
"about",
"ordinary",
"situations",
".",
"the",
"dynam... |
ACL | CoDraw: Collaborative Drawing as a Testbed for Grounded Goal-driven Communication | In this work, we propose a goal-driven collaborative task that combines language, perception, and action. Specifically, we develop a Collaborative image-Drawing game between two agents, called CoDraw. Our game is grounded in a virtual world that contains movable clip art objects. The game involves two players: a Teller... | 19a58dc3b3e37bb8d01518489c9ed6d3 | 2,019 | [
"in this work , we propose a goal - driven collaborative task that combines language , perception , and action .",
"specifically , we develop a collaborative image - drawing game between two agents , called codraw .",
"our game is grounded in a virtual world that contains movable clip art objects .",
"the gam... | [
{
"event_type": "PRP",
"arguments": [
{
"text": "we",
"nugget_type": "OG",
"argument_type": "Proposer",
"tokens": [
"we"
],
"offsets": [
4
]
},
{
"text": "goal - driven collaborative task",
"nugget_... | [
"in",
"this",
"work",
",",
"we",
"propose",
"a",
"goal",
"-",
"driven",
"collaborative",
"task",
"that",
"combines",
"language",
",",
"perception",
",",
"and",
"action",
".",
"specifically",
",",
"we",
"develop",
"a",
"collaborative",
"image",
"-",
"drawing"... |
ACL | Agreement Prediction of Arguments in Cyber Argumentation for Detecting Stance Polarity and Intensity | In online debates, users express different levels of agreement/disagreement with one another’s arguments and ideas. Often levels of agreement/disagreement are implicit in the text, and must be predicted to analyze collective opinions. Existing stance detection methods predict the polarity of a post’s stance toward a to... | 4bc656b7889c55e60753471f801fc28f | 2,020 | [
"in online debates , users express different levels of agreement / disagreement with one another ’ s arguments and ideas .",
"often levels of agreement / disagreement are implicit in the text , and must be predicted to analyze collective opinions .",
"existing stance detection methods predict the polarity of a ... | [
{
"event_type": "RWS",
"arguments": [
{
"text": "existing stance detection methods",
"nugget_type": "APP",
"argument_type": "Subject",
"tokens": [
"existing",
"stance",
"detection",
"methods"
],
"offsets": [
... | [
"in",
"online",
"debates",
",",
"users",
"express",
"different",
"levels",
"of",
"agreement",
"/",
"disagreement",
"with",
"one",
"another",
"’",
"s",
"arguments",
"and",
"ideas",
".",
"often",
"levels",
"of",
"agreement",
"/",
"disagreement",
"are",
"implicit... |
ACL | Cross-Linguistic Syntactic Evaluation of Word Prediction Models | A range of studies have concluded that neural word prediction models can distinguish grammatical from ungrammatical sentences with high accuracy. However, these studies are based primarily on monolingual evidence from English. To investigate how these models’ ability to learn syntax varies by language, we introduce CLA... | 4024e4374fbbdeeaf9876c77e688b1dd | 2,020 | [
"a range of studies have concluded that neural word prediction models can distinguish grammatical from ungrammatical sentences with high accuracy .",
"however , these studies are based primarily on monolingual evidence from english .",
"to investigate how these models ’ ability to learn syntax varies by languag... | [
{
"event_type": "RWS",
"arguments": [
{
"text": "neural word prediction models",
"nugget_type": "APP",
"argument_type": "Subject",
"tokens": [
"neural",
"word",
"prediction",
"models"
],
"offsets": [
7,
... | [
"a",
"range",
"of",
"studies",
"have",
"concluded",
"that",
"neural",
"word",
"prediction",
"models",
"can",
"distinguish",
"grammatical",
"from",
"ungrammatical",
"sentences",
"with",
"high",
"accuracy",
".",
"however",
",",
"these",
"studies",
"are",
"based",
... |
ACL | The Grammar-Learning Trajectories of Neural Language Models | The learning trajectories of linguistic phenomena in humans provide insight into linguistic representation, beyond what can be gleaned from inspecting the behavior of an adult speaker. To apply a similar approach to analyze neural language models (NLM), it is first necessary to establish that different models are simil... | 129fd030d8b379d83206704cd6baf3b8 | 2,022 | [
"the learning trajectories of linguistic phenomena in humans provide insight into linguistic representation , beyond what can be gleaned from inspecting the behavior of an adult speaker .",
"to apply a similar approach to analyze neural language models ( nlm ) , it is first necessary to establish that different m... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "neural language models",
"nugget_type": "APP",
"argument_type": "Target",
"tokens": [
"neural",
"language",
"models"
],
"offsets": [
35,
36,
37
... | [
"the",
"learning",
"trajectories",
"of",
"linguistic",
"phenomena",
"in",
"humans",
"provide",
"insight",
"into",
"linguistic",
"representation",
",",
"beyond",
"what",
"can",
"be",
"gleaned",
"from",
"inspecting",
"the",
"behavior",
"of",
"an",
"adult",
"speaker"... |
ACL | Zero-shot Word Sense Disambiguation using Sense Definition Embeddings | Word Sense Disambiguation (WSD) is a long-standing but open problem in Natural Language Processing (NLP). WSD corpora are typically small in size, owing to an expensive annotation process. Current supervised WSD methods treat senses as discrete labels and also resort to predicting the Most-Frequent-Sense (MFS) for word... | 4fa288c1297f9b74d4d1b03aca8c3160 | 2,019 | [
"word sense disambiguation ( wsd ) is a long - standing but open problem in natural language processing ( nlp ) .",
"wsd corpora are typically small in size , owing to an expensive annotation process .",
"current supervised wsd methods treat senses as discrete labels and also resort to predicting the most - fre... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "word sense disambiguation",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"word",
"sense",
"disambiguation"
],
"offsets": [
0,
1,
... | [
"word",
"sense",
"disambiguation",
"(",
"wsd",
")",
"is",
"a",
"long",
"-",
"standing",
"but",
"open",
"problem",
"in",
"natural",
"language",
"processing",
"(",
"nlp",
")",
".",
"wsd",
"corpora",
"are",
"typically",
"small",
"in",
"size",
",",
"owing",
... |
ACL | Math Word Problem Solving with Explicit Numerical Values | In recent years, math word problem solving has received considerable attention and achieved promising results, but previous methods rarely take numerical values into consideration. Most methods treat the numerical values in the problems as number symbols, and ignore the prominent role of the numerical values in solving... | 36bef989c090d2729b8a0e4df62db71d | 2,021 | [
"in recent years , math word problem solving has received considerable attention and achieved promising results , but previous methods rarely take numerical values into consideration .",
"most methods treat the numerical values in the problems as number symbols , and ignore the prominent role of the numerical val... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "math word problem solving",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"math",
"word",
"problem",
"solving"
],
"offsets": [
4,
... | [
"in",
"recent",
"years",
",",
"math",
"word",
"problem",
"solving",
"has",
"received",
"considerable",
"attention",
"and",
"achieved",
"promising",
"results",
",",
"but",
"previous",
"methods",
"rarely",
"take",
"numerical",
"values",
"into",
"consideration",
".",... |
ACL | Predicting Depression in Screening Interviews from Latent Categorization of Interview Prompts | Accurately diagnosing depression is difficult– requiring time-intensive interviews, assessments, and analysis. Hence, automated methods that can assess linguistic patterns in these interviews could help psychiatric professionals make faster, more informed decisions about diagnosis. We propose JLPC, a model that analyze... | a2a4cac8c830c71c588fbc66ae0e89a4 | 2,020 | [
"accurately diagnosing depression is difficult – requiring time - intensive interviews , assessments , and analysis .",
"hence , automated methods that can assess linguistic patterns in these interviews could help psychiatric professionals make faster , more informed decisions about diagnosis .",
"we propose jl... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "depression",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"depression"
],
"offsets": [
2
]
}
],
"trigger": {
"text": "diagnosing",
"tok... | [
"accurately",
"diagnosing",
"depression",
"is",
"difficult",
"–",
"requiring",
"time",
"-",
"intensive",
"interviews",
",",
"assessments",
",",
"and",
"analysis",
".",
"hence",
",",
"automated",
"methods",
"that",
"can",
"assess",
"linguistic",
"patterns",
"in",
... |
ACL | To Test Machine Comprehension, Start by Defining Comprehension | Many tasks aim to measure machine reading comprehension (MRC), often focusing on question types presumed to be difficult. Rarely, however, do task designers start by considering what systems should in fact comprehend. In this paper we make two key contributions. First, we argue that existing approaches do not adequatel... | ecf4f2d4880a6848844afec025113ae1 | 2,020 | [
"many tasks aim to measure machine reading comprehension ( mrc ) , often focusing on question types presumed to be difficult .",
"rarely , however , do task designers start by considering what systems should in fact comprehend .",
"in this paper we make two key contributions .",
"first , we argue that existin... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "machine reading comprehension",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"machine",
"reading",
"comprehension"
],
"offsets": [
5,
6,
... | [
"many",
"tasks",
"aim",
"to",
"measure",
"machine",
"reading",
"comprehension",
"(",
"mrc",
")",
",",
"often",
"focusing",
"on",
"question",
"types",
"presumed",
"to",
"be",
"difficult",
".",
"rarely",
",",
"however",
",",
"do",
"task",
"designers",
"start",... |
ACL | Self-supervised Semantic-driven Phoneme Discovery for Zero-resource Speech Recognition | Phonemes are defined by their relationship to words: changing a phoneme changes the word. Learning a phoneme inventory with little supervision has been a longstanding challenge with important applications to under-resourced speech technology. In this paper, we bridge the gap between the linguistic and statistical defin... | c582ab83aa292d35bc2fe767ad8b7c38 | 2,022 | [
"phonemes are defined by their relationship to words : changing a phoneme changes the word .",
"learning a phoneme inventory with little supervision has been a longstanding challenge with important applications to under - resourced speech technology .",
"in this paper , we bridge the gap between the linguistic ... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "phonemes",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"phonemes"
],
"offsets": [
0
]
}
],
"trigger": {
"text": "defined",
"tokens": [... | [
"phonemes",
"are",
"defined",
"by",
"their",
"relationship",
"to",
"words",
":",
"changing",
"a",
"phoneme",
"changes",
"the",
"word",
".",
"learning",
"a",
"phoneme",
"inventory",
"with",
"little",
"supervision",
"has",
"been",
"a",
"longstanding",
"challenge",... |
ACL | NeuInfer: Knowledge Inference on N-ary Facts | Knowledge inference on knowledge graph has attracted extensive attention, which aims to find out connotative valid facts in knowledge graph and is very helpful for improving the performance of many downstream applications. However, researchers have mainly poured attention to knowledge inference on binary facts. The stu... | 9820eceaae4c792ace795385a5cc65c4 | 2,020 | [
"knowledge inference on knowledge graph has attracted extensive attention , which aims to find out connotative valid facts in knowledge graph and is very helpful for improving the performance of many downstream applications .",
"however , researchers have mainly poured attention to knowledge inference on binary f... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "knowledge inference",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"knowledge",
"inference"
],
"offsets": [
0,
1
]
}
],
"trigge... | [
"knowledge",
"inference",
"on",
"knowledge",
"graph",
"has",
"attracted",
"extensive",
"attention",
",",
"which",
"aims",
"to",
"find",
"out",
"connotative",
"valid",
"facts",
"in",
"knowledge",
"graph",
"and",
"is",
"very",
"helpful",
"for",
"improving",
"the",... |
ACL | Cross-Modality Relevance for Reasoning on Language and Vision | This work deals with the challenge of learning and reasoning over language and vision data for the related downstream tasks such as visual question answering (VQA) and natural language for visual reasoning (NLVR). We design a novel cross-modality relevance module that is used in an end-to-end framework to learn the rel... | c951999e5fcfedf4aa616bd1444a3610 | 2,020 | [
"this work deals with the challenge of learning and reasoning over language and vision data for the related downstream tasks such as visual question answering ( vqa ) and natural language for visual reasoning ( nlvr ) .",
"we design a novel cross - modality relevance module that is used in an end - to - end frame... | [
{
"event_type": "WKS",
"arguments": [
{
"text": "related downstream tasks",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"related",
"downstream",
"tasks"
],
"offsets": [
17,
18,
... | [
"this",
"work",
"deals",
"with",
"the",
"challenge",
"of",
"learning",
"and",
"reasoning",
"over",
"language",
"and",
"vision",
"data",
"for",
"the",
"related",
"downstream",
"tasks",
"such",
"as",
"visual",
"question",
"answering",
"(",
"vqa",
")",
"and",
"... |
ACL | Extracting Symptoms and their Status from Clinical Conversations | This paper describes novel models tailored for a new application, that of extracting the symptoms mentioned in clinical conversations along with their status. Lack of any publicly available corpus in this privacy-sensitive domain led us to develop our own corpus, consisting of about 3K conversations annotated by profes... | 530d106ee1eaf49d87d82975ed72740f | 2,019 | [
"this paper describes novel models tailored for a new application , that of extracting the symptoms mentioned in clinical conversations along with their status .",
"lack of any publicly available corpus in this privacy - sensitive domain led us to develop our own corpus , consisting of about 3k conversations anno... | [
{
"event_type": "PRP",
"arguments": [
{
"text": "own corpus",
"nugget_type": "DST",
"argument_type": "Content",
"tokens": [
"own",
"corpus"
],
"offsets": [
42,
43
]
}
],
"trigger": {
"te... | [
"this",
"paper",
"describes",
"novel",
"models",
"tailored",
"for",
"a",
"new",
"application",
",",
"that",
"of",
"extracting",
"the",
"symptoms",
"mentioned",
"in",
"clinical",
"conversations",
"along",
"with",
"their",
"status",
".",
"lack",
"of",
"any",
"pu... |
ACL | Explaining Black Box Predictions and Unveiling Data Artifacts through Influence Functions | Modern deep learning models for NLP are notoriously opaque. This has motivated the development of methods for interpreting such models, e.g., via gradient-based saliency maps or the visualization of attention weights. Such approaches aim to provide explanations for a particular model prediction by highlighting importan... | 1613928091f7e967987318afb013b390 | 2,020 | [
"modern deep learning models for nlp are notoriously opaque .",
"this has motivated the development of methods for interpreting such models , e . g . , via gradient - based saliency maps or the visualization of attention weights .",
"such approaches aim to provide explanations for a particular model prediction ... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "modern deep learning models",
"nugget_type": "APP",
"argument_type": "Target",
"tokens": [
"modern",
"deep",
"learning",
"models"
],
"offsets": [
0,
... | [
"modern",
"deep",
"learning",
"models",
"for",
"nlp",
"are",
"notoriously",
"opaque",
".",
"this",
"has",
"motivated",
"the",
"development",
"of",
"methods",
"for",
"interpreting",
"such",
"models",
",",
"e",
".",
"g",
".",
",",
"via",
"gradient",
"-",
"ba... |
ACL | NILE : Natural Language Inference with Faithful Natural Language Explanations | The recent growth in the popularity and success of deep learning models on NLP classification tasks has accompanied the need for generating some form of natural language explanation of the predicted labels. Such generated natural language (NL) explanations are expected to be faithful, i.e., they should correlate well w... | 70ccf84a3e04e117d1ee383f6a6894f2 | 2,020 | [
"the recent growth in the popularity and success of deep learning models on nlp classification tasks has accompanied the need for generating some form of natural language explanation of the predicted labels .",
"such generated natural language ( nl ) explanations are expected to be faithful , i . e . , they shoul... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "natural language explanation",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"natural",
"language",
"explanation"
],
"offsets": [
25,
26,
... | [
"the",
"recent",
"growth",
"in",
"the",
"popularity",
"and",
"success",
"of",
"deep",
"learning",
"models",
"on",
"nlp",
"classification",
"tasks",
"has",
"accompanied",
"the",
"need",
"for",
"generating",
"some",
"form",
"of",
"natural",
"language",
"explanatio... |
ACL | TIGS: An Inference Algorithm for Text Infilling with Gradient Search | Text infilling aims at filling in the missing part of a sentence or paragraph, which has been applied to a variety of real-world natural language generation scenarios. Given a well-trained sequential generative model, it is challenging for its unidirectional decoder to generate missing symbols conditioned on the past a... | 2198a0155d186ab9487d615b068df9c5 | 2,019 | [
"text infilling aims at filling in the missing part of a sentence or paragraph , which has been applied to a variety of real - world natural language generation scenarios .",
"given a well - trained sequential generative model , it is challenging for its unidirectional decoder to generate missing symbols conditio... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "text infilling",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"text",
"infilling"
],
"offsets": [
0,
1
]
}
],
"trigger": {
... | [
"text",
"infilling",
"aims",
"at",
"filling",
"in",
"the",
"missing",
"part",
"of",
"a",
"sentence",
"or",
"paragraph",
",",
"which",
"has",
"been",
"applied",
"to",
"a",
"variety",
"of",
"real",
"-",
"world",
"natural",
"language",
"generation",
"scenarios"... |
ACL | Modeling Financial Analysts’ Decision Making via the Pragmatics and Semantics of Earnings Calls | Every fiscal quarter, companies hold earnings calls in which company executives respond to questions from analysts. After these calls, analysts often change their price target recommendations, which are used in equity re- search reports to help investors make deci- sions. In this paper, we examine analysts’ decision ma... | 8ca66ec2e6b8c0972452f8db17092cd4 | 2,019 | [
"every fiscal quarter , companies hold earnings calls in which company executives respond to questions from analysts .",
"after these calls , analysts often change their price target recommendations , which are used in equity re - search reports to help investors make deci - sions .",
"in this paper , we examin... | [
{
"event_type": "WKS",
"arguments": [
{
"text": "we",
"nugget_type": "OG",
"argument_type": "Researcher",
"tokens": [
"we"
],
"offsets": [
51
]
},
{
"text": "analysts ’ decision making behavior",
"n... | [
"every",
"fiscal",
"quarter",
",",
"companies",
"hold",
"earnings",
"calls",
"in",
"which",
"company",
"executives",
"respond",
"to",
"questions",
"from",
"analysts",
".",
"after",
"these",
"calls",
",",
"analysts",
"often",
"change",
"their",
"price",
"target",... |
ACL | Incorporating Priors with Feature Attribution on Text Classification | Feature attribution methods, proposed recently, help users interpret the predictions of complex models. Our approach integrates feature attributions into the objective function to allow machine learning practitioners to incorporate priors in model building. To demonstrate the effectiveness our technique, we apply it to... | 2772eb1011e461bb5593ca3888921471 | 2,019 | [
"feature attribution methods , proposed recently , help users interpret the predictions of complex models .",
"our approach integrates feature attributions into the objective function to allow machine learning practitioners to incorporate priors in model building .",
"to demonstrate the effectiveness our techni... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "feature attribution methods",
"nugget_type": "APP",
"argument_type": "Target",
"tokens": [
"feature",
"attribution",
"methods"
],
"offsets": [
0,
1,
... | [
"feature",
"attribution",
"methods",
",",
"proposed",
"recently",
",",
"help",
"users",
"interpret",
"the",
"predictions",
"of",
"complex",
"models",
".",
"our",
"approach",
"integrates",
"feature",
"attributions",
"into",
"the",
"objective",
"function",
"to",
"al... |
ACL | Compare to The Knowledge: Graph Neural Fake News Detection with External Knowledge | Nowadays, fake news detection, which aims to verify whether a news document is trusted or fake, has become urgent and important. Most existing methods rely heavily on linguistic and semantic features from the news content, and fail to effectively exploit external knowledge which could help determine whether the news do... | 17041a2c185634d2f05e4f2f103a351f | 2,021 | [
"nowadays , fake news detection , which aims to verify whether a news document is trusted or fake , has become urgent and important .",
"most existing methods rely heavily on linguistic and semantic features from the news content , and fail to effectively exploit external knowledge which could help determine whet... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "fake news detection",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"fake",
"news",
"detection"
],
"offsets": [
2,
3,
4
]
... | [
"nowadays",
",",
"fake",
"news",
"detection",
",",
"which",
"aims",
"to",
"verify",
"whether",
"a",
"news",
"document",
"is",
"trusted",
"or",
"fake",
",",
"has",
"become",
"urgent",
"and",
"important",
".",
"most",
"existing",
"methods",
"rely",
"heavily",
... |
ACL | FastBERT: a Self-distilling BERT with Adaptive Inference Time | Pre-trained language models like BERT have proven to be highly performant. However, they are often computationally expensive in many practical scenarios, for such heavy models can hardly be readily implemented with limited resources. To improve their efficiency with an assured model performance, we propose a novel spee... | 67e15913ca395176bdf83a586ed0c5e6 | 2,020 | [
"pre - trained language models like bert have proven to be highly performant .",
"however , they are often computationally expensive in many practical scenarios , for such heavy models can hardly be readily implemented with limited resources .",
"to improve their efficiency with an assured model performance , w... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "pre - trained language models",
"nugget_type": "APP",
"argument_type": "Target",
"tokens": [
"pre",
"-",
"trained",
"language",
"models"
],
"offsets": [
... | [
"pre",
"-",
"trained",
"language",
"models",
"like",
"bert",
"have",
"proven",
"to",
"be",
"highly",
"performant",
".",
"however",
",",
"they",
"are",
"often",
"computationally",
"expensive",
"in",
"many",
"practical",
"scenarios",
",",
"for",
"such",
"heavy",... |
ACL | A Neural Model for Joint Document and Snippet Ranking in Question Answering for Large Document Collections | Question answering (QA) systems for large document collections typically use pipelines that (i) retrieve possibly relevant documents, (ii) re-rank them, (iii) rank paragraphs or other snippets of the top-ranked documents, and (iv) select spans of the top-ranked snippets as exact answers. Pipelines are conceptually simp... | 114f2c2366f80caba86d9586bf4683cf | 2,021 | [
"question answering ( qa ) systems for large document collections typically use pipelines that ( i ) retrieve possibly relevant documents , ( ii ) re - rank them , ( iii ) rank paragraphs or other snippets of the top - ranked documents , and ( iv ) select spans of the top - ranked snippets as exact answers .",
"p... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "question answering systems",
"nugget_type": "APP",
"argument_type": "Target",
"tokens": [
"question",
"answering",
"systems"
],
"offsets": [
0,
1,
... | [
"question",
"answering",
"(",
"qa",
")",
"systems",
"for",
"large",
"document",
"collections",
"typically",
"use",
"pipelines",
"that",
"(",
"i",
")",
"retrieve",
"possibly",
"relevant",
"documents",
",",
"(",
"ii",
")",
"re",
"-",
"rank",
"them",
",",
"("... |
ACL | Celebrity Profiling | Celebrities are among the most prolific users of social media, promoting their personas and rallying followers. This activity is closely tied to genuine writing samples, which makes them worthy research subjects in many respects, not least profiling. With this paper we introduce the Webis Celebrity Corpus 2019. For its... | be1eb9bfd9198bef100dedc416f34695 | 2,019 | [
"celebrities are among the most prolific users of social media , promoting their personas and rallying followers .",
"this activity is closely tied to genuine writing samples , which makes them worthy research subjects in many respects , not least profiling .",
"with this paper we introduce the webis celebrity ... | [
{
"event_type": "WKS",
"arguments": [
{
"text": "we",
"nugget_type": "OG",
"argument_type": "Researcher",
"tokens": [
"we"
],
"offsets": [
45
]
},
{
"text": "webis celebrity corpus 2019",
"nugget_ty... | [
"celebrities",
"are",
"among",
"the",
"most",
"prolific",
"users",
"of",
"social",
"media",
",",
"promoting",
"their",
"personas",
"and",
"rallying",
"followers",
".",
"this",
"activity",
"is",
"closely",
"tied",
"to",
"genuine",
"writing",
"samples",
",",
"wh... |
ACL | Neural-Symbolic Solver for Math Word Problems with Auxiliary Tasks | Previous math word problem solvers following the encoder-decoder paradigm fail to explicitly incorporate essential math symbolic constraints, leading to unexplainable and unreasonable predictions. Herein, we propose Neural-Symbolic Solver (NS-Solver) to explicitly and seamlessly incorporate different levels of symbolic... | 3fa10296e808ce5ab9426c9978b6ba3a | 2,021 | [
"previous math word problem solvers following the encoder - decoder paradigm fail to explicitly incorporate essential math symbolic constraints , leading to unexplainable and unreasonable predictions .",
"herein , we propose neural - symbolic solver ( ns - solver ) to explicitly and seamlessly incorporate differe... | [
{
"event_type": "RWF",
"arguments": [
{
"text": "previous math word problem solvers following the encoder - decoder paradigm",
"nugget_type": "APP",
"argument_type": "Concern",
"tokens": [
"previous",
"math",
"word",
"problem",
... | [
"previous",
"math",
"word",
"problem",
"solvers",
"following",
"the",
"encoder",
"-",
"decoder",
"paradigm",
"fail",
"to",
"explicitly",
"incorporate",
"essential",
"math",
"symbolic",
"constraints",
",",
"leading",
"to",
"unexplainable",
"and",
"unreasonable",
"pre... |
ACL | Imitation Learning for Non-Autoregressive Neural Machine Translation | Non-autoregressive translation models (NAT) have achieved impressive inference speedup. A potential issue of the existing NAT algorithms, however, is that the decoding is conducted in parallel, without directly considering previous context. In this paper, we propose an imitation learning framework for non-autoregressiv... | 030a7f4c3782cbc87643f2aa68a7594c | 2,019 | [
"non - autoregressive translation models ( nat ) have achieved impressive inference speedup .",
"a potential issue of the existing nat algorithms , however , is that the decoding is conducted in parallel , without directly considering previous context .",
"in this paper , we propose an imitation learning framew... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "non - autoregressive translation models",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"non",
"-",
"autoregressive",
"translation",
"models"
],
... | [
"non",
"-",
"autoregressive",
"translation",
"models",
"(",
"nat",
")",
"have",
"achieved",
"impressive",
"inference",
"speedup",
".",
"a",
"potential",
"issue",
"of",
"the",
"existing",
"nat",
"algorithms",
",",
"however",
",",
"is",
"that",
"the",
"decoding"... |
ACL | Dynamic Sampling Strategies for Multi-Task Reading Comprehension | Building general reading comprehension systems, capable of solving multiple datasets at the same time, is a recent aspirational goal in the research community. Prior work has focused on model architecture or generalization to held out datasets, and largely passed over the particulars of the multi-task learning set up. ... | e3d522c194a348ea4bf534467d9ec89a | 2,020 | [
"building general reading comprehension systems , capable of solving multiple datasets at the same time , is a recent aspirational goal in the research community .",
"prior work has focused on model architecture or generalization to held out datasets , and largely passed over the particulars of the multi - task l... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "general reading comprehension systems",
"nugget_type": "APP",
"argument_type": "Target",
"tokens": [
"general",
"reading",
"comprehension",
"systems"
],
"offsets": [... | [
"building",
"general",
"reading",
"comprehension",
"systems",
",",
"capable",
"of",
"solving",
"multiple",
"datasets",
"at",
"the",
"same",
"time",
",",
"is",
"a",
"recent",
"aspirational",
"goal",
"in",
"the",
"research",
"community",
".",
"prior",
"work",
"h... |
ACL | Learning from Miscellaneous Other-Class Words for Few-shot Named Entity Recognition | Few-shot Named Entity Recognition (NER) exploits only a handful of annotations to iden- tify and classify named entity mentions. Pro- totypical network shows superior performance on few-shot NER. However, existing prototyp- ical methods fail to differentiate rich seman- tics in other-class words, which will aggravate o... | bec35f92be214119f4997f4ee34142e6 | 2,021 | [
"few - shot named entity recognition ( ner ) exploits only a handful of annotations to identify and classify named entity mentions .",
"prototypical network shows superior performance on few - shot ner .",
"however , existing prototypical methods fail to differentiate rich semantics in other - class words , whi... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "few - shot ner",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"few",
"-",
"shot",
"ner"
],
"offsets": [
0,
1,
2,
... | [
"few",
"-",
"shot",
"named",
"entity",
"recognition",
"(",
"ner",
")",
"exploits",
"only",
"a",
"handful",
"of",
"annotations",
"to",
"identify",
"and",
"classify",
"named",
"entity",
"mentions",
".",
"prototypical",
"network",
"shows",
"superior",
"performance"... |
ACL | Automatic Poetry Generation from Prosaic Text | In the last few years, a number of successful approaches have emerged that are able to adequately model various aspects of natural language. In particular, language models based on neural networks have improved the state of the art with regard to predictive language modeling, while topic models are successful at captur... | f2ddd475a84ad982db937682e1237431 | 2,020 | [
"in the last few years , a number of successful approaches have emerged that are able to adequately model various aspects of natural language .",
"in particular , language models based on neural networks have improved the state of the art with regard to predictive language modeling , while topic models are succes... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "natural language",
"nugget_type": "FEA",
"argument_type": "Target",
"tokens": [
"natural",
"language"
],
"offsets": [
22,
23
]
}
],
"trigger": ... | [
"in",
"the",
"last",
"few",
"years",
",",
"a",
"number",
"of",
"successful",
"approaches",
"have",
"emerged",
"that",
"are",
"able",
"to",
"adequately",
"model",
"various",
"aspects",
"of",
"natural",
"language",
".",
"in",
"particular",
",",
"language",
"mo... |
ACL | Meta-Learning for Fast Cross-Lingual Adaptation in Dependency Parsing | Meta-learning, or learning to learn, is a technique that can help to overcome resource scarcity in cross-lingual NLP problems, by enabling fast adaptation to new tasks. We apply model-agnostic meta-learning (MAML) to the task of cross-lingual dependency parsing. We train our model on a diverse set of languages to learn... | e259c0033779d5ed14eef9fc1668fb92 | 2,022 | [
"meta - learning , or learning to learn , is a technique that can help to overcome resource scarcity in cross - lingual nlp problems , by enabling fast adaptation to new tasks .",
"we apply model - agnostic meta - learning ( maml ) to the task of cross - lingual dependency parsing .",
"we train our model on a d... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "meta - learning",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"meta",
"-",
"learning"
],
"offsets": [
0,
1,
2
]
}
... | [
"meta",
"-",
"learning",
",",
"or",
"learning",
"to",
"learn",
",",
"is",
"a",
"technique",
"that",
"can",
"help",
"to",
"overcome",
"resource",
"scarcity",
"in",
"cross",
"-",
"lingual",
"nlp",
"problems",
",",
"by",
"enabling",
"fast",
"adaptation",
"to"... |
ACL | Translate-Train Embracing Translationese Artifacts | Translate-train is a general training approach to multilingual tasks. The key idea is to use the translator of the target language to generate training data to mitigate the gap between the source and target languages. However, its performance is often hampered by the artifacts in the translated texts (translationese). ... | 4d7080ad489918b61bd03cad80576bbb | 2,022 | [
"translate - train is a general training approach to multilingual tasks .",
"the key idea is to use the translator of the target language to generate training data to mitigate the gap between the source and target languages .",
"however , its performance is often hampered by the artifacts in the translated text... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "translate - train",
"nugget_type": "APP",
"argument_type": "Target",
"tokens": [
"translate",
"-",
"train"
],
"offsets": [
0,
1,
2
]
... | [
"translate",
"-",
"train",
"is",
"a",
"general",
"training",
"approach",
"to",
"multilingual",
"tasks",
".",
"the",
"key",
"idea",
"is",
"to",
"use",
"the",
"translator",
"of",
"the",
"target",
"language",
"to",
"generate",
"training",
"data",
"to",
"mitigat... |
ACL | Why Didn’t You Listen to Me? Comparing User Control of Human-in-the-Loop Topic Models | To address the lack of comparative evaluation of Human-in-the-Loop Topic Modeling (HLTM) systems, we implement and evaluate three contrasting HLTM modeling approaches using simulation experiments. These approaches extend previously proposed frameworks, including constraints and informed prior-based methods. Users shoul... | 48a0af1d9ecfc3515b87d0d327d07263 | 2,019 | [
"to address the lack of comparative evaluation of human - in - the - loop topic modeling ( hltm ) systems , we implement and evaluate three contrasting hltm modeling approaches using simulation experiments .",
"these approaches extend previously proposed frameworks , including constraints and informed prior - bas... | [
{
"event_type": "PRP",
"arguments": [
{
"text": "address",
"nugget_type": "E-PUR",
"argument_type": "Target",
"tokens": [
"address"
],
"offsets": [
1
]
},
{
"text": "we",
"nugget_type": "OG",
... | [
"to",
"address",
"the",
"lack",
"of",
"comparative",
"evaluation",
"of",
"human",
"-",
"in",
"-",
"the",
"-",
"loop",
"topic",
"modeling",
"(",
"hltm",
")",
"systems",
",",
"we",
"implement",
"and",
"evaluate",
"three",
"contrasting",
"hltm",
"modeling",
"... |
ACL | SUPERB-SG: Enhanced Speech processing Universal PERformance Benchmark for Semantic and Generative Capabilities | Transfer learning has proven to be crucial in advancing the state of speech and natural language processing research in recent years. In speech, a model pre-trained by self-supervised learning transfers remarkably well on multiple tasks. However, the lack of a consistent evaluation methodology is limiting towards a hol... | 29c59578814ef0fd47cbfac3a3717743 | 2,022 | [
"transfer learning has proven to be crucial in advancing the state of speech and natural language processing research in recent years .",
"in speech , a model pre - trained by self - supervised learning transfers remarkably well on multiple tasks .",
"however , the lack of a consistent evaluation methodology is... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "transfer learning",
"nugget_type": "APP",
"argument_type": "Target",
"tokens": [
"transfer",
"learning"
],
"offsets": [
0,
1
]
}
],
"trigger": ... | [
"transfer",
"learning",
"has",
"proven",
"to",
"be",
"crucial",
"in",
"advancing",
"the",
"state",
"of",
"speech",
"and",
"natural",
"language",
"processing",
"research",
"in",
"recent",
"years",
".",
"in",
"speech",
",",
"a",
"model",
"pre",
"-",
"trained",... |
ACL | On Faithfulness and Factuality in Abstractive Summarization | It is well known that the standard likelihood training and approximate decoding objectives in neural text generation models lead to less human-like responses for open-ended tasks such as language modeling and story generation. In this paper we have analyzed limitations of these models for abstractive document summariza... | 81833d2f921e0e327d26c9c2ce26779f | 2,020 | [
"it is well known that the standard likelihood training and approximate decoding objectives in neural text generation models lead to less human - like responses for open - ended tasks such as language modeling and story generation .",
"in this paper we have analyzed limitations of these models for abstractive doc... | [
{
"event_type": "RWF",
"arguments": [
{
"text": "less human - like responses",
"nugget_type": "WEA",
"argument_type": "Fault",
"tokens": [
"less",
"human",
"-",
"like",
"responses"
],
"offsets": [
... | [
"it",
"is",
"well",
"known",
"that",
"the",
"standard",
"likelihood",
"training",
"and",
"approximate",
"decoding",
"objectives",
"in",
"neural",
"text",
"generation",
"models",
"lead",
"to",
"less",
"human",
"-",
"like",
"responses",
"for",
"open",
"-",
"ende... |
ACL | Fire Burns, Sword Cuts: Commonsense Inductive Bias for Exploration in Text-based Games | Text-based games (TGs) are exciting testbeds for developing deep reinforcement learning techniques due to their partially observed environments and large action spaces. In these games, the agent learns to explore the environment via natural language interactions with the game simulator. A fundamental challenge in TGs i... | ffae0f0c14e5e52697d1af97ea0b9387 | 2,022 | [
"text - based games ( tgs ) are exciting testbeds for developing deep reinforcement learning techniques due to their partially observed environments and large action spaces .",
"in these games , the agent learns to explore the environment via natural language interactions with the game simulator .",
"a fundamen... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "text - based games",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"text",
"-",
"based",
"games"
],
"offsets": [
0,
1,
2... | [
"text",
"-",
"based",
"games",
"(",
"tgs",
")",
"are",
"exciting",
"testbeds",
"for",
"developing",
"deep",
"reinforcement",
"learning",
"techniques",
"due",
"to",
"their",
"partially",
"observed",
"environments",
"and",
"large",
"action",
"spaces",
".",
"in",
... |
ACL | Phonetic and Visual Priors for Decipherment of Informal Romanization | Informal romanization is an idiosyncratic process used by humans in informal digital communication to encode non-Latin script languages into Latin character sets found on common keyboards. Character substitution choices differ between users but have been shown to be governed by the same main principles observed across ... | 1ae7c92bf82d5fd4e24e441080b688b4 | 2,020 | [
"informal romanization is an idiosyncratic process used by humans in informal digital communication to encode non - latin script languages into latin character sets found on common keyboards .",
"character substitution choices differ between users but have been shown to be governed by the same main principles obs... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "informal romanization",
"nugget_type": "MOD",
"argument_type": "Target",
"tokens": [
"informal",
"romanization"
],
"offsets": [
0,
1
]
},
{
... | [
"informal",
"romanization",
"is",
"an",
"idiosyncratic",
"process",
"used",
"by",
"humans",
"in",
"informal",
"digital",
"communication",
"to",
"encode",
"non",
"-",
"latin",
"script",
"languages",
"into",
"latin",
"character",
"sets",
"found",
"on",
"common",
"... |
ACL | Improving Multi-label Malevolence Detection in Dialogues through Multi-faceted Label Correlation Enhancement | A dialogue response is malevolent if it is grounded in negative emotions, inappropriate behavior, or an unethical value basis in terms of content and dialogue acts. The detection of malevolent dialogue responses is attracting growing interest. Current research on detecting dialogue malevolence has limitations in terms ... | 57af0d28e9f37e0230f0a6376bd775a1 | 2,022 | [
"a dialogue response is malevolent if it is grounded in negative emotions , inappropriate behavior , or an unethical value basis in terms of content and dialogue acts .",
"the detection of malevolent dialogue responses is attracting growing interest .",
"current research on detecting dialogue malevolence has li... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "malevolent dialogue responses",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"malevolent",
"dialogue",
"responses"
],
"offsets": [
32,
33,
... | [
"a",
"dialogue",
"response",
"is",
"malevolent",
"if",
"it",
"is",
"grounded",
"in",
"negative",
"emotions",
",",
"inappropriate",
"behavior",
",",
"or",
"an",
"unethical",
"value",
"basis",
"in",
"terms",
"of",
"content",
"and",
"dialogue",
"acts",
".",
"th... |
ACL | MLQA: Evaluating Cross-lingual Extractive Question Answering | Question answering (QA) models have shown rapid progress enabled by the availability of large, high-quality benchmark datasets. Such annotated datasets are difficult and costly to collect, and rarely exist in languages other than English, making building QA systems that work well in other languages challenging. In orde... | 0b484322d6f8500355a754c5b0b3d5e6 | 2,020 | [
"question answering ( qa ) models have shown rapid progress enabled by the availability of large , high - quality benchmark datasets .",
"such annotated datasets are difficult and costly to collect , and rarely exist in languages other than english , making building qa systems that work well in other languages ch... | [
{
"event_type": "RWF",
"arguments": [
{
"text": "difficult",
"nugget_type": "DEG",
"argument_type": "Extent",
"tokens": [
"difficult"
],
"offsets": [
27
]
},
{
"text": "costly",
"nugget_type": "DEG"... | [
"question",
"answering",
"(",
"qa",
")",
"models",
"have",
"shown",
"rapid",
"progress",
"enabled",
"by",
"the",
"availability",
"of",
"large",
",",
"high",
"-",
"quality",
"benchmark",
"datasets",
".",
"such",
"annotated",
"datasets",
"are",
"difficult",
"and... |
ACL | Joint Type Inference on Entities and Relations via Graph Convolutional Networks | We develop a new paradigm for the task of joint entity relation extraction. It first identifies entity spans, then performs a joint inference on entity types and relation types. To tackle the joint type inference task, we propose a novel graph convolutional network (GCN) running on an entity-relation bipartite graph. B... | af7b9800454b65ed3f40dc92a06dfa5b | 2,019 | [
"we develop a new paradigm for the task of joint entity relation extraction .",
"it first identifies entity spans , then performs a joint inference on entity types and relation types .",
"to tackle the joint type inference task , we propose a novel graph convolutional network ( gcn ) running on an entity - rela... | [
{
"event_type": "PRP",
"arguments": [
{
"text": "we",
"nugget_type": "OG",
"argument_type": "Proposer",
"tokens": [
"we"
],
"offsets": [
0
]
},
{
"text": "paradigm",
"nugget_type": "APP",
"a... | [
"we",
"develop",
"a",
"new",
"paradigm",
"for",
"the",
"task",
"of",
"joint",
"entity",
"relation",
"extraction",
".",
"it",
"first",
"identifies",
"entity",
"spans",
",",
"then",
"performs",
"a",
"joint",
"inference",
"on",
"entity",
"types",
"and",
"relati... |
ACL | Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data | The success of the large neural language models on many NLP tasks is exciting. However, we find that these successes sometimes lead to hype in which these models are being described as “understanding” language or capturing “meaning”. In this position paper, we argue that a system trained only on form has a priori no wa... | 389e47dc5f8f227618f6de71f0bd01d0 | 2,020 | [
"the success of the large neural language models on many nlp tasks is exciting .",
"however , we find that these successes sometimes lead to hype in which these models are being described as “ understanding ” language or capturing “ meaning ” .",
"in this position paper , we argue that a system trained only on ... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "large neural language models",
"nugget_type": "APP",
"argument_type": "Target",
"tokens": [
"large",
"neural",
"language",
"models"
],
"offsets": [
4,
... | [
"the",
"success",
"of",
"the",
"large",
"neural",
"language",
"models",
"on",
"many",
"nlp",
"tasks",
"is",
"exciting",
".",
"however",
",",
"we",
"find",
"that",
"these",
"successes",
"sometimes",
"lead",
"to",
"hype",
"in",
"which",
"these",
"models",
"a... |
ACL | A Wind of Change: Detecting and Evaluating Lexical Semantic Change across Times and Domains | We perform an interdisciplinary large-scale evaluation for detecting lexical semantic divergences in a diachronic and in a synchronic task: semantic sense changes across time, and semantic sense changes across domains. Our work addresses the superficialness and lack of comparison in assessing models of diachronic lexic... | 29b40f20276d41476b4e49ed716dab66 | 2,019 | [
"we perform an interdisciplinary large - scale evaluation for detecting lexical semantic divergences in a diachronic and in a synchronic task : semantic sense changes across time , and semantic sense changes across domains .",
"our work addresses the superficialness and lack of comparison in assessing models of d... | [
{
"event_type": "WKS",
"arguments": [
{
"text": "we",
"nugget_type": "OG",
"argument_type": "Researcher",
"tokens": [
"we"
],
"offsets": [
0
]
},
{
"text": "in a diachronic and in a synchronic task",
... | [
"we",
"perform",
"an",
"interdisciplinary",
"large",
"-",
"scale",
"evaluation",
"for",
"detecting",
"lexical",
"semantic",
"divergences",
"in",
"a",
"diachronic",
"and",
"in",
"a",
"synchronic",
"task",
":",
"semantic",
"sense",
"changes",
"across",
"time",
","... |
ACL | Finding Structural Knowledge in Multimodal-BERT | In this work, we investigate the knowledge learned in the embeddings of multimodal-BERT models. More specifically, we probe their capabilities of storing the grammatical structure of linguistic data and the structure learned over objects in visual data. To reach that goal, we first make the inherent structure of langua... | 65725d21968a9690a2e369b44789548c | 2,022 | [
"in this work , we investigate the knowledge learned in the embeddings of multimodal - bert models .",
"more specifically , we probe their capabilities of storing the grammatical structure of linguistic data and the structure learned over objects in visual data .",
"to reach that goal , we first make the inhere... | [
{
"event_type": "WKS",
"arguments": [
{
"text": "we",
"nugget_type": "OG",
"argument_type": "Researcher",
"tokens": [
"we"
],
"offsets": [
4
]
},
{
"text": "knowledge learned",
"nugget_type": "TAK",... | [
"in",
"this",
"work",
",",
"we",
"investigate",
"the",
"knowledge",
"learned",
"in",
"the",
"embeddings",
"of",
"multimodal",
"-",
"bert",
"models",
".",
"more",
"specifically",
",",
"we",
"probe",
"their",
"capabilities",
"of",
"storing",
"the",
"grammatical"... |
ACL | Evaluating Gender Bias in Machine Translation | We present the first challenge set and evaluation protocol for the analysis of gender bias in machine translation (MT). Our approach uses two recent coreference resolution datasets composed of English sentences which cast participants into non-stereotypical gender roles (e.g., “The doctor asked the nurse to help her in... | ea4b051d05af67a14bb82de49c3dd3c9 | 2,019 | [
"we present the first challenge set and evaluation protocol for the analysis of gender bias in machine translation ( mt ) .",
"our approach uses two recent coreference resolution datasets composed of english sentences which cast participants into non - stereotypical gender roles ( e . g . , “ the doctor asked the... | [
{
"event_type": "PRP",
"arguments": [
{
"text": "we",
"nugget_type": "OG",
"argument_type": "Proposer",
"tokens": [
"we"
],
"offsets": [
0
]
},
{
"text": "analysis of gender bias",
"nugget_type": "T... | [
"we",
"present",
"the",
"first",
"challenge",
"set",
"and",
"evaluation",
"protocol",
"for",
"the",
"analysis",
"of",
"gender",
"bias",
"in",
"machine",
"translation",
"(",
"mt",
")",
".",
"our",
"approach",
"uses",
"two",
"recent",
"coreference",
"resolution"... |
ACL | Meaning to Form: Measuring Systematicity as Information | A longstanding debate in semiotics centers on the relationship between linguistic signs and their corresponding semantics: is there an arbitrary relationship between a word form and its meaning, or does some systematic phenomenon pervade? For instance, does the character bigram ‘gl’ have any systematic relationship to ... | aa5270d5cd462560c07eff2bd71a19d5 | 2,019 | [
"a longstanding debate in semiotics centers on the relationship between linguistic signs and their corresponding semantics : is there an arbitrary relationship between a word form and its meaning , or does some systematic phenomenon pervade ?",
"for instance , does the character bigram ‘ gl ’ have any systematic ... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "semiotics",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"semiotics"
],
"offsets": [
4
]
}
],
"trigger": {
"text": "centers",
"tokens":... | [
"a",
"longstanding",
"debate",
"in",
"semiotics",
"centers",
"on",
"the",
"relationship",
"between",
"linguistic",
"signs",
"and",
"their",
"corresponding",
"semantics",
":",
"is",
"there",
"an",
"arbitrary",
"relationship",
"between",
"a",
"word",
"form",
"and",
... |
ACL | Lexical Semantic Change Discovery | While there is a large amount of research in the field of Lexical Semantic Change Detection, only few approaches go beyond a standard benchmark evaluation of existing models. In this paper, we propose a shift of focus from change detection to change discovery, i.e., discovering novel word senses over time from the full... | cc25fd05c46717975a1d0633e4562eb4 | 2,021 | [
"while there is a large amount of research in the field of lexical semantic change detection , only few approaches go beyond a standard benchmark evaluation of existing models .",
"in this paper , we propose a shift of focus from change detection to change discovery , i . e . , discovering novel word senses over ... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "lexical semantic change detection",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"lexical",
"semantic",
"change",
"detection"
],
"offsets": [
... | [
"while",
"there",
"is",
"a",
"large",
"amount",
"of",
"research",
"in",
"the",
"field",
"of",
"lexical",
"semantic",
"change",
"detection",
",",
"only",
"few",
"approaches",
"go",
"beyond",
"a",
"standard",
"benchmark",
"evaluation",
"of",
"existing",
"models"... |
ACL | Open Domain Question Answering with A Unified Knowledge Interface | The retriever-reader framework is popular for open-domain question answering (ODQA) due to its ability to use explicit knowledge.Although prior work has sought to increase the knowledge coverage by incorporating structured knowledge beyond text, accessing heterogeneous knowledge sources through a unified interface rema... | 7cd6c256aaaa2b7c066eeb2f160b4398 | 2,022 | [
"the retriever - reader framework is popular for open - domain question answering ( odqa ) due to its ability to use explicit knowledge .",
"although prior work has sought to increase the knowledge coverage by incorporating structured knowledge beyond text , accessing heterogeneous knowledge sources through a uni... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "open - domain question answering",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"open",
"-",
"domain",
"question",
"answering"
],
"offsets"... | [
"the",
"retriever",
"-",
"reader",
"framework",
"is",
"popular",
"for",
"open",
"-",
"domain",
"question",
"answering",
"(",
"odqa",
")",
"due",
"to",
"its",
"ability",
"to",
"use",
"explicit",
"knowledge",
".",
"although",
"prior",
"work",
"has",
"sought",
... |
ACL | Selecting Backtranslated Data from Multiple Sources for Improved Neural Machine Translation | Machine translation (MT) has benefited from using synthetic training data originating from translating monolingual corpora, a technique known as backtranslation. Combining backtranslated data from different sources has led to better results than when using such data in isolation. In this work we analyse the impact that... | 62e857c2d600698fac96a1fd7834a923 | 2,020 | [
"machine translation ( mt ) has benefited from using synthetic training data originating from translating monolingual corpora , a technique known as backtranslation .",
"combining backtranslated data from different sources has led to better results than when using such data in isolation .",
"in this work we ana... | [
{
"event_type": "FAC",
"arguments": [
{
"text": "availing of data selection",
"nugget_type": "APP",
"argument_type": "Subject",
"tokens": [
"availing",
"of",
"data",
"selection"
],
"offsets": [
199,
... | [
"machine",
"translation",
"(",
"mt",
")",
"has",
"benefited",
"from",
"using",
"synthetic",
"training",
"data",
"originating",
"from",
"translating",
"monolingual",
"corpora",
",",
"a",
"technique",
"known",
"as",
"backtranslation",
".",
"combining",
"backtranslated... |
ACL | UniTranSeR: A Unified Transformer Semantic Representation Framework for Multimodal Task-Oriented Dialog System | As a more natural and intelligent interaction manner, multimodal task-oriented dialog system recently has received great attention and many remarkable progresses have been achieved. Nevertheless, almost all existing studies follow the pipeline to first learn intra-modal features separately and then conduct simple featu... | 4677ce992d836b56f1bdb917ac343eff | 2,022 | [
"as a more natural and intelligent interaction manner , multimodal task - oriented dialog system recently has received great attention and many remarkable progresses have been achieved .",
"nevertheless , almost all existing studies follow the pipeline to first learn intra - modal features separately and then con... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "multimodal task - oriented dialog system",
"nugget_type": "APP",
"argument_type": "Target",
"tokens": [
"multimodal",
"task",
"-",
"oriented",
"dialog",
"system"... | [
"as",
"a",
"more",
"natural",
"and",
"intelligent",
"interaction",
"manner",
",",
"multimodal",
"task",
"-",
"oriented",
"dialog",
"system",
"recently",
"has",
"received",
"great",
"attention",
"and",
"many",
"remarkable",
"progresses",
"have",
"been",
"achieved",... |
ACL | In Neural Machine Translation, What Does Transfer Learning Transfer? | Transfer learning improves quality for low-resource machine translation, but it is unclear what exactly it transfers. We perform several ablation studies that limit information transfer, then measure the quality impact across three language pairs to gain a black-box understanding of transfer learning. Word embeddings p... | 41ac46c294536cb3efad9594da0a5331 | 2,020 | [
"transfer learning improves quality for low - resource machine translation , but it is unclear what exactly it transfers .",
"we perform several ablation studies that limit information transfer , then measure the quality impact across three language pairs to gain a black - box understanding of transfer learning .... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "transfer learning",
"nugget_type": "APP",
"argument_type": "Target",
"tokens": [
"transfer",
"learning"
],
"offsets": [
0,
1
]
}
],
"trigger": ... | [
"transfer",
"learning",
"improves",
"quality",
"for",
"low",
"-",
"resource",
"machine",
"translation",
",",
"but",
"it",
"is",
"unclear",
"what",
"exactly",
"it",
"transfers",
".",
"we",
"perform",
"several",
"ablation",
"studies",
"that",
"limit",
"information... |
ACL | Mention Flags (MF): Constraining Transformer-based Text Generators | This paper focuses on Seq2Seq (S2S) constrained text generation where the text generator is constrained to mention specific words which are inputs to the encoder in the generated outputs. Pre-trained S2S models or a Copy Mechanism are trained to copy the surface tokens from encoders to decoders, but they cannot guarant... | e827914ae4ee7d96eea6f64da8678c45 | 2,021 | [
"this paper focuses on seq2seq ( s2s ) constrained text generation where the text generator is constrained to mention specific words which are inputs to the encoder in the generated outputs .",
"pre - trained s2s models or a copy mechanism are trained to copy the surface tokens from encoders to decoders , but the... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "seq2seq ( s2s ) constrained text generation",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"seq2seq",
"(",
"s2s",
")",
"constrained",
"text",
... | [
"this",
"paper",
"focuses",
"on",
"seq2seq",
"(",
"s2s",
")",
"constrained",
"text",
"generation",
"where",
"the",
"text",
"generator",
"is",
"constrained",
"to",
"mention",
"specific",
"words",
"which",
"are",
"inputs",
"to",
"the",
"encoder",
"in",
"the",
... |
ACL | Impact of Evaluation Methodologies on Code Summarization | There has been a growing interest in developing machine learning (ML) models for code summarization tasks, e.g., comment generation and method naming. Despite substantial increase in the effectiveness of ML models, the evaluation methodologies, i.e., the way people split datasets into training, validation, and test set... | d686a8aeb9a9f90d7f14bf3656d0663f | 2,022 | [
"there has been a growing interest in developing machine learning ( ml ) models for code summarization tasks , e . g . , comment generation and method naming .",
"despite substantial increase in the effectiveness of ml models , the evaluation methodologies , i . e . , the way people split datasets into training ,... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "code summarization tasks",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"code",
"summarization",
"tasks"
],
"offsets": [
15,
16,
... | [
"there",
"has",
"been",
"a",
"growing",
"interest",
"in",
"developing",
"machine",
"learning",
"(",
"ml",
")",
"models",
"for",
"code",
"summarization",
"tasks",
",",
"e",
".",
"g",
".",
",",
"comment",
"generation",
"and",
"method",
"naming",
".",
"despit... |
ACL | Neural-DINF: A Neural Network based Framework for Measuring Document Influence | Measuring the scholarly impact of a document without citations is an important and challenging problem. Existing approaches such as Document Influence Model (DIM) are based on dynamic topic models, which only consider the word frequency change. In this paper, we use both frequency changes and word semantic shifts to me... | af7a898af8422ec83f3a89db0c77eacd | 2,020 | [
"measuring the scholarly impact of a document without citations is an important and challenging problem .",
"existing approaches such as document influence model ( dim ) are based on dynamic topic models , which only consider the word frequency change .",
"in this paper , we use both frequency changes and word ... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "scholarly impact",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"scholarly",
"impact"
],
"offsets": [
2,
3
]
}
],
"trigger": {
... | [
"measuring",
"the",
"scholarly",
"impact",
"of",
"a",
"document",
"without",
"citations",
"is",
"an",
"important",
"and",
"challenging",
"problem",
".",
"existing",
"approaches",
"such",
"as",
"document",
"influence",
"model",
"(",
"dim",
")",
"are",
"based",
... |
ACL | An Exploratory Analysis of Multilingual Word-Level Quality Estimation with Cross-Lingual Transformers | Most studies on word-level Quality Estimation (QE) of machine translation focus on language-specific models. The obvious disadvantages of these approaches are the need for labelled data for each language pair and the high cost required to maintain several language-specific models. To overcome these problems, we explore... | fdcd020e35ef9d54bf6a1a76814386ff | 2,021 | [
"most studies on word - level quality estimation ( qe ) of machine translation focus on language - specific models .",
"the obvious disadvantages of these approaches are the need for labelled data for each language pair and the high cost required to maintain several language - specific models .",
"to overcome t... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "word - level quality estimation of machine translation",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"word",
"-",
"level",
"quality",
"estimation",
... | [
"most",
"studies",
"on",
"word",
"-",
"level",
"quality",
"estimation",
"(",
"qe",
")",
"of",
"machine",
"translation",
"focus",
"on",
"language",
"-",
"specific",
"models",
".",
"the",
"obvious",
"disadvantages",
"of",
"these",
"approaches",
"are",
"the",
"... |
ACL | Zero-Shot Semantic Parsing for Instructions | We consider a zero-shot semantic parsing task: parsing instructions into compositional logical forms, in domains that were not seen during training. We present a new dataset with 1,390 examples from 7 application domains (e.g. a calendar or a file manager), each example consisting of a triplet: (a) the application’s in... | ae7e1be89b2ddf22adc34b643cf25f78 | 2,019 | [
"we consider a zero - shot semantic parsing task : parsing instructions into compositional logical forms , in domains that were not seen during training .",
"we present a new dataset with 1 , 390 examples from 7 application domains ( e . g . a calendar or a file manager ) , each example consisting of a triplet : ... | [
{
"event_type": "WKS",
"arguments": [
{
"text": "we",
"nugget_type": "OG",
"argument_type": "Researcher",
"tokens": [
"we"
],
"offsets": [
0
]
},
{
"text": "zero - shot semantic parsing task",
"nugg... | [
"we",
"consider",
"a",
"zero",
"-",
"shot",
"semantic",
"parsing",
"task",
":",
"parsing",
"instructions",
"into",
"compositional",
"logical",
"forms",
",",
"in",
"domains",
"that",
"were",
"not",
"seen",
"during",
"training",
".",
"we",
"present",
"a",
"new... |
ACL | Modeling U.S. State-Level Policies by Extracting Winners and Losers from Legislative Texts | Decisions on state-level policies have a deep effect on many aspects of our everyday life, such as health-care and education access. However, there is little understanding of how these policies and decisions are being formed in the legislative process. We take a data-driven approach by decoding the impact of legislatio... | 8d6c990f5486a9488ca0b6efefaac6b5 | 2,022 | [
"decisions on state - level policies have a deep effect on many aspects of our everyday life , such as health - care and education access .",
"however , there is little understanding of how these policies and decisions are being formed in the legislative process .",
"we take a data - driven approach by decoding... | [
{
"event_type": "PRP",
"arguments": [
{
"text": "we",
"nugget_type": "OG",
"argument_type": "Proposer",
"tokens": [
"we"
],
"offsets": [
47
]
},
{
"text": "data - driven approach",
"nugget_type": "A... | [
"decisions",
"on",
"state",
"-",
"level",
"policies",
"have",
"a",
"deep",
"effect",
"on",
"many",
"aspects",
"of",
"our",
"everyday",
"life",
",",
"such",
"as",
"health",
"-",
"care",
"and",
"education",
"access",
".",
"however",
",",
"there",
"is",
"li... |
ACL | Attend to Medical Ontologies: Content Selection for Clinical Abstractive Summarization | Sequence-to-sequence (seq2seq) network is a well-established model for text summarization task. It can learn to produce readable content; however, it falls short in effectively identifying key regions of the source. In this paper, we approach the content selection problem for clinical abstractive summarization by augme... | d8357628e2e50735903bcb4364f532f6 | 2,020 | [
"sequence - to - sequence ( seq2seq ) network is a well - established model for text summarization task .",
"it can learn to produce readable content ; however , it falls short in effectively identifying key regions of the source .",
"in this paper , we approach the content selection problem for clinical abstra... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "text summarization task",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"text",
"summarization",
"task"
],
"offsets": [
16,
17,
18... | [
"sequence",
"-",
"to",
"-",
"sequence",
"(",
"seq2seq",
")",
"network",
"is",
"a",
"well",
"-",
"established",
"model",
"for",
"text",
"summarization",
"task",
".",
"it",
"can",
"learn",
"to",
"produce",
"readable",
"content",
";",
"however",
",",
"it",
... |
ACL | Rare and Zero-shot Word Sense Disambiguation using Z-Reweighting | Word sense disambiguation (WSD) is a crucial problem in the natural language processing (NLP) community. Current methods achieve decent performance by utilizing supervised learning and large pre-trained language models. However, the imbalanced training dataset leads to poor performance on rare senses and zero-shot sens... | eb299bbeef63037c2239c943047e6dbe | 2,022 | [
"word sense disambiguation ( wsd ) is a crucial problem in the natural language processing ( nlp ) community .",
"current methods achieve decent performance by utilizing supervised learning and large pre - trained language models .",
"however , the imbalanced training dataset leads to poor performance on rare s... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "word sense disambiguation",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"word",
"sense",
"disambiguation"
],
"offsets": [
0,
1,
... | [
"word",
"sense",
"disambiguation",
"(",
"wsd",
")",
"is",
"a",
"crucial",
"problem",
"in",
"the",
"natural",
"language",
"processing",
"(",
"nlp",
")",
"community",
".",
"current",
"methods",
"achieve",
"decent",
"performance",
"by",
"utilizing",
"supervised",
... |
ACL | Assessing Emoji Use in Modern Text Processing Tools | Emojis have become ubiquitous in digital communication, due to their visual appeal as well as their ability to vividly convey human emotion, among other factors. This also leads to an increased need for systems and tools to operate on text containing emojis. In this study, we assess this support by considering test set... | ffa8a740d1f7c5fc055e7820eb37db26 | 2,021 | [
"emojis have become ubiquitous in digital communication , due to their visual appeal as well as their ability to vividly convey human emotion , among other factors .",
"this also leads to an increased need for systems and tools to operate on text containing emojis .",
"in this study , we assess this support by ... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "emojis",
"nugget_type": "FEA",
"argument_type": "Target",
"tokens": [
"emojis"
],
"offsets": [
0
]
}
],
"trigger": {
"text": "become",
"tokens": [
... | [
"emojis",
"have",
"become",
"ubiquitous",
"in",
"digital",
"communication",
",",
"due",
"to",
"their",
"visual",
"appeal",
"as",
"well",
"as",
"their",
"ability",
"to",
"vividly",
"convey",
"human",
"emotion",
",",
"among",
"other",
"factors",
".",
"this",
"... |
ACL | A Unified Generative Framework for Various NER Subtasks | Named Entity Recognition (NER) is the task of identifying spans that represent entities in sentences. Whether the entity spans are nested or discontinuous, the NER task can be categorized into the flat NER, nested NER, and discontinuous NER subtasks. These subtasks have been mainly solved by the token-level sequence la... | 2788b5150d6505aff6628dc993aa0deb | 2,021 | [
"named entity recognition ( ner ) is the task of identifying spans that represent entities in sentences .",
"whether the entity spans are nested or discontinuous , the ner task can be categorized into the flat ner , nested ner , and discontinuous ner subtasks .",
"these subtasks have been mainly solved by the t... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "named entity recognition",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"named",
"entity",
"recognition"
],
"offsets": [
0,
1,
2
... | [
"named",
"entity",
"recognition",
"(",
"ner",
")",
"is",
"the",
"task",
"of",
"identifying",
"spans",
"that",
"represent",
"entities",
"in",
"sentences",
".",
"whether",
"the",
"entity",
"spans",
"are",
"nested",
"or",
"discontinuous",
",",
"the",
"ner",
"ta... |
ACL | Cross-language Sentence Selection via Data Augmentation and Rationale Training | This paper proposes an approach to cross-language sentence selection in a low-resource setting. It uses data augmentation and negative sampling techniques on noisy parallel sentence data to directly learn a cross-lingual embedding-based query relevance model. Results show that this approach performs as well as or bette... | 21622162ce2fb48e3e9df6e701ee34e5 | 2,021 | [
"this paper proposes an approach to cross - language sentence selection in a low - resource setting .",
"it uses data augmentation and negative sampling techniques on noisy parallel sentence data to directly learn a cross - lingual embedding - based query relevance model .",
"results show that this approach per... | [
{
"event_type": "PRP",
"arguments": [
{
"text": "approach to cross - language sentence selection",
"nugget_type": "APP",
"argument_type": "Content",
"tokens": [
"approach",
"to",
"cross",
"-",
"language",
"sent... | [
"this",
"paper",
"proposes",
"an",
"approach",
"to",
"cross",
"-",
"language",
"sentence",
"selection",
"in",
"a",
"low",
"-",
"resource",
"setting",
".",
"it",
"uses",
"data",
"augmentation",
"and",
"negative",
"sampling",
"techniques",
"on",
"noisy",
"parall... |
ACL | Text Categorization by Learning Predominant Sense of Words as Auxiliary Task | Distributions of the senses of words are often highly skewed and give a strong influence of the domain of a document. This paper follows the assumption and presents a method for text categorization by leveraging the predominant sense of words depending on the domain, i.e., domain-specific senses. The key idea is that t... | 3376ead9dd2db0dc6ffd819b9a4fbdf1 | 2,019 | [
"distributions of the senses of words are often highly skewed and give a strong influence of the domain of a document .",
"this paper follows the assumption and presents a method for text categorization by leveraging the predominant sense of words depending on the domain , i . e . , domain - specific senses .",
... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "distributions of the senses of words",
"nugget_type": "FEA",
"argument_type": "Target",
"tokens": [
"distributions",
"of",
"the",
"senses",
"of",
"words"
... | [
"distributions",
"of",
"the",
"senses",
"of",
"words",
"are",
"often",
"highly",
"skewed",
"and",
"give",
"a",
"strong",
"influence",
"of",
"the",
"domain",
"of",
"a",
"document",
".",
"this",
"paper",
"follows",
"the",
"assumption",
"and",
"presents",
"a",
... |
ACL | USR: An Unsupervised and Reference Free Evaluation Metric for Dialog Generation | The lack of meaningful automatic evaluation metrics for dialog has impeded open-domain dialog research. Standard language generation metrics have been shown to be ineffective for evaluating dialog models. To this end, this paper presents USR, an UnSupervised and Reference-free evaluation metric for dialog. USR is a ref... | b42517fec9d38afd3c3227fa290dbe7d | 2,020 | [
"the lack of meaningful automatic evaluation metrics for dialog has impeded open - domain dialog research .",
"standard language generation metrics have been shown to be ineffective for evaluating dialog models .",
"to this end , this paper presents usr , an unsupervised and reference - free evaluation metric f... | [
{
"event_type": "RWF",
"arguments": [
{
"text": "lack of meaningful automatic evaluation metrics",
"nugget_type": "WEA",
"argument_type": "Fault",
"tokens": [
"lack",
"of",
"meaningful",
"automatic",
"evaluation",
... | [
"the",
"lack",
"of",
"meaningful",
"automatic",
"evaluation",
"metrics",
"for",
"dialog",
"has",
"impeded",
"open",
"-",
"domain",
"dialog",
"research",
".",
"standard",
"language",
"generation",
"metrics",
"have",
"been",
"shown",
"to",
"be",
"ineffective",
"fo... |
ACL | Learning to Reason Deductively: Math Word Problem Solving as Complex Relation Extraction | Solving math word problems requires deductive reasoning over the quantities in the text. Various recent research efforts mostly relied on sequence-to-sequence or sequence-to-tree models to generate mathematical expressions without explicitly performing relational reasoning between quantities in the given context. While... | d2bf64e6c945d5a40891daed104f8b40 | 2,022 | [
"solving math word problems requires deductive reasoning over the quantities in the text .",
"various recent research efforts mostly relied on sequence - to - sequence or sequence - to - tree models to generate mathematical expressions without explicitly performing relational reasoning between quantities in the g... | [
{
"event_type": "ITT",
"arguments": [
{
"text": "math word problems",
"nugget_type": "TAK",
"argument_type": "Target",
"tokens": [
"math",
"word",
"problems"
],
"offsets": [
1,
2,
3
]
... | [
"solving",
"math",
"word",
"problems",
"requires",
"deductive",
"reasoning",
"over",
"the",
"quantities",
"in",
"the",
"text",
".",
"various",
"recent",
"research",
"efforts",
"mostly",
"relied",
"on",
"sequence",
"-",
"to",
"-",
"sequence",
"or",
"sequence",
... |
ACL | QAConv: Question Answering on Informative Conversations | This paper introduces QAConv, a new question answering (QA) dataset that uses conversations as a knowledge source. We focus on informative conversations, including business emails, panel discussions, and work channels. Unlike open-domain and task-oriented dialogues, these conversations are usually long, complex, asynch... | af121e8942557787d3243974dbd6ae81 | 2,022 | [
"this paper introduces qaconv , a new question answering ( qa ) dataset that uses conversations as a knowledge source .",
"we focus on informative conversations , including business emails , panel discussions , and work channels .",
"unlike open - domain and task - oriented dialogues , these conversations are u... | [
{
"event_type": "PRP",
"arguments": [
{
"text": "question answering dataset",
"nugget_type": "DST",
"argument_type": "Content",
"tokens": [
"question",
"answering",
"dataset"
],
"offsets": [
7,
8,
... | [
"this",
"paper",
"introduces",
"qaconv",
",",
"a",
"new",
"question",
"answering",
"(",
"qa",
")",
"dataset",
"that",
"uses",
"conversations",
"as",
"a",
"knowledge",
"source",
".",
"we",
"focus",
"on",
"informative",
"conversations",
",",
"including",
"busine... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.