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naacl_data_prog

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[ "End-to-end approaches for sequence tasks are becoming increasingly popular.", "Yet for complex sequence tasks, like speech translation, systems that cascade several models trained on sub-tasks have shown to be superior, suggesting that the compositionality of cascaded systems simplifies learning and enables soph...
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[ "Pre-trained models for programming languages have recently demonstrated great success on code intelligence.", "To support both code-related understanding and generation tasks, recent works attempt to pre-train unified encoder-decoder models.", "However, such encoder-decoder framework is sub-optimal for auto-re...
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[ "Multimodal pre-training has propelled great advancement in vision-and-language research.", "These large-scale pre-trained models, although successful, fatefully suffer from slow inference speed due to enormous computation cost mainly from cross-modal attention in Transformer architecture.", "When applied to re...
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[ "Event Detection (ED) aims to recognize mentions of events (i.e., event triggers) and their types in text.", "Recently, several ED datasets in various domains have been proposed.", "However, the major limitation of these resources is the lack of enough training data for individual event types which hinders the ...
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[ "While large language models have shown exciting progress on several NLP benchmarks, evaluating their ability for complex analogical reasoning remains under-explored.", "Here, we introduce a high-quality crowdsourced dataset of narratives for employing proverbs in context as a benchmark for abstract language unde...
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[ "Warning: This paper contains explicit statements", "statements of offensive stereotypes which may be", "upsetting Much work on biases in natural language processing has addressed biases linked to the social and cultural experience of English speaking individuals in the United States.", "We seek to widen the ...
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[ "Although recent neural conversation models have shown great potential, they often generate bland and generic responses.", "While various approaches have been explored to diversify the output of the conversation model, the improvement often comes at the cost of decreased relevance (Zhang et al., 2018).", "In th...
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[ "We develop a formal hierarchy of the expressive capacity of RNN architectures.", "The hierarchy is based on two formal properties: space complexity, which measures the RNN's memory, and rational recurrence, defined as whether the recurrent update can be described by a weighted finite-state machine.", "We place...
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[ "Temporal factors are tied to the growth of facts in realistic applications, such as the progress of diseases and the development of political situation, therefore, research on Temporal Knowledge Graph (TKG) attracks much attention.", "In TKG, relation patterns inherent with temporality are required to be studied...
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[ "Leveraging domain knowledge is an effective strategy for enhancing the quality of inferred low-dimensional representations of documents by topic models.", "In this paper, we develop topic modeling with knowledge graph embedding (TMKGE), a Bayesian nonparametric model to employ knowledge graph (KG) embedding in t...
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[ "We present a framework for learning hierarchical policies from demonstrations, using sparse natural language annotations to guide the discovery of reusable skills for autonomous decision-making.", "We formulate a generative model of action sequences in which goals generate sequences of high-level subtask descrip...
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[ "We study the problem of Event Causality Identification (ECI) to detect causal relation between event mention pairs in text.", "Although deep learning models have recently shown state-of-the-art performance for ECI, they are limited to the intra-sentence setting where event mention pairs are presented in the same...
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[ "In recent years there has been a burgeoning interest in the use of computational methods to distinguish between elicited speech samples produced by patients with dementia, and those from healthy controls.", "The difference between perplexity estimates from two neural language models (LMs) one trained on transcri...
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[ "Cross-lingual summarization is the task of generating a summary in one language given a text in a different language.", "Previous works on cross-lingual summarization mainly focus on using pipeline methods or training an end-to-end model using the translated parallel data.", "However, it is a big challenge for...
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[ "This paper proposes a simple and effective algorithm for incorporating lexical constraints in neural machine translation.", "Previous work either required re-training existing models with the lexical constraints or incorporating them during beam search decoding with significantly higher computational overheads."...
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[ "Individual differences in speakers are reflected in their language use as well as in their interests and opinions.", "Characterizing these differences can be useful in human-computer interaction, as well as analysis of human-human conversations.", "In this work, we introduce a neural model for learning a dynam...
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[ "Advanced pre-trained models for text representation have achieved state-of-the-art performance on various text classification tasks.", "However, the discrepancy between the semantic similarity of texts and labelling standards affects classifiers, i.e. leading to lower performance in cases where classifiers shoul...
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[ "Recent work has attempted to enhance vector space representations using information from structured semantic resources.", "This process, dubbed retrofitting Faruqui et al. (2015), has yielded improvements in word similarity performance.", "Research has largely focused on the retrofitting algorithm, or on the k...
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[ "Medical imaging plays a significant role in clinical practice of medical diagnosis, where the text reports of the images are essential in understanding them and facilitating later treatments.", "By generating the reports automatically, it is beneficial to help lighten the burden of radiologists and significantly...
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[ "Speech pre-training has primarily demonstrated efficacy on classification tasks, while its capability of generating novel speech, similar to how GPT-2 can generate coherent paragraphs, has barely been explored.", "Generative Spoken Language Modeling (GSLM) (Lakho-tia et al., 2021) is the only prior work addressi...
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[ "Abstract", "We introduce the well-established social scientific concept of social solidarity and its contestation, anti-solidarity, as a new problem setting to supervised machine learning in NLP to assess how European solidarity discourses changed before and after the COVID-19 outbreak was declared a global pand...
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[ "The task of Dialogue Act Classification (DAC) that purports to capture communicative intent has been studied extensively.", "But these studies limit themselves to text.", "Non-verbal features (change of tone, facial expressions etc.) can provide cues to identify DAs, thus stressing the benefit of incorporating...
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[ "Automatic extraction of product attribute values is an important enabling technology in e-Commerce platforms.", "This task is usually modeled using sequence labeling architectures, with several extensions to handle multi-attribute extraction.", "One line of previous work constructs attribute-specific models, t...
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[ "Most dominant neural machine translation (NMT) models are restricted to make predictions only according to the local context of preceding words in a left-to-right manner.", "Although many previous studies try to incorporate global information into NMT models, there still exist limitations on how to effectively e...
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[ "Answering complex questions is a time-consuming activity for humans that requires reasoning and integration of information.", "Recent work on reading comprehension made headway in answering simple questions, but tackling complex questions is still an ongoing research challenge.", "Conversely, semantic parsers ...
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[ "Unsupervised bilingual lexicon induction is the task of inducing word translations from monolingual corpora of two languages.", "Recent methods are mostly based on unsupervised cross-lingual word embeddings, the key to which is to find initial solutions of word translations, followed by the learning and refineme...
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[ "Opinion target extraction and opinion words extraction are two fundamental subtasks in Aspect Based Sentiment Analysis (ABSA).", "Recently, many methods have made progress on these two tasks.", "However, few works aim at extracting opinion targets and opinion words as pairs.", "In this paper, we propose a no...
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[ "Abstract", "The code and data are available at https: //github.com/wenhuchen/LogicNLG .", "Neural natural language generation (NLG) models have recently shown remarkable progress in fluency and coherence.", "However, existing studies on neural NLG are primarily focused on surface-level realizations with limi...
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[ "Recent advances in prompt-based learning have shown strong results on few-shot text classification by using cloze-style templates.", "Similar attempts have been made on named entity recognition (NER) which manually design templates to predict entity types for every text span in a sentence.", "However, such met...
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[ "NLP community is currently investing a lot more research and resources into development of deep learning models than training data.", "While we have made a lot of progress, it is now clear that our models learn all kinds of spurious patterns, social biases, and annotation artifacts.", "Algorithmic solutions ha...
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[ "Text-based adventure games provide a platform on which to explore reinforcement learning in the context of a combinatorial action space, such as natural language.", "We present a deep reinforcement learning architecture that represents the game state as a knowledge graph which is learned during exploration.", ...
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[ "Entity alignment (EA) aims to find the equivalent entity pairs between KGs, which is a crucial step for integrating multi-source KGs.", "For a long time, most researchers have regarded EA as a pure graph representation learning task and focused on improving graph encoders while paying little attention to the dec...
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[ "Abstract Story visualization is an underexplored task that falls at the intersection of many important research directions in both computer vision and natural language processing.", "In this task, given a series of natural language captions which compose a story, an agent must generate a sequence of images that ...
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[ "Opinion role labeling (ORL) is an important task for fine-grained opinion mining, which identifies important opinion arguments such as holder and target for a given opinion trigger.", "The task is highly correlative with semantic role labeling (SRL), which identifies important semantic arguments such as agent an...
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[ "We teach goal-driven agents to interactively act and speak in situated environments by training on generated curriculums.", "Our agents operate in LIGHT (Urbanek et al., 2019)a large-scale crowd-sourced fantasy text adventure game wherein an agent perceives and interacts with the world through textual natural la...
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[ "In many natural language processing applications, identifying predictive text can be as important as the predictions themselves.", "When predicting medical diagnoses, for example, identifying predictive content in clinical notes not only enhances interpretability, but also allows unknown, descriptive ( i.e., tex...
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[ "Recent works of opinion expression identification (OEI) rely heavily on the quality and scale of the manually-constructed training corpus, which could be extremely difficult to satisfy.", "Crowdsourcing is one practical solution for this problem, aiming to create a large-scale but quality-unguaranteed corpus.", ...
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[ "We pioneer the first extractive summarization-based collaborative filtering model called ESCOFILT.", "Our proposed model specifically produces extractive summaries for each item and user.", "Unlike other types of explanations, summary-level explanations closely resemble real-life explanations.", "The strengt...
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[ "Sentence compression methods based on LSTM can generate fluent compressed sentences.", "However, the performance of these methods is significantly degraded when compressing long sentences since it does not explicitly handle syntactic features.", "To solve this problem, we propose a higher-order syntactic atten...
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[ "State-of-the-art pre-trained language models have been shown to memorise facts and perform well with limited amounts of training data.", "To gain a better understanding of how these models learn, we study their generalisation and memorisation capabilities in noisy and low-resource scenarios.", "We find that th...
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[ "Based on the recently proposed transferable dialogue state generator (TRADE) (Wu et al., 2019) that predicts dialogue states from utterance-concatenated dialogue context, we propose a multi-task learning model with a simple yet effective utterance tagging technique and a bidirectional language model as an auxiliar...
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[ "User language data can contain highly sensitive personal content.", "As such, it is imperative to offer users a strong and interpretable privacy guarantee when learning from their data.", "In this work, we propose SentDP: pure local differential privacy at the sentence level for a single user document.", "We...
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[ "Although deep learning models have brought tremendous advancements to the field of open-domain dialogue response generation, recent research results have revealed that the trained models have undesirable generation behaviors, such as malicious responses and generic (bor-ing) responses.", "In this work, we propos...
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[ "We present a word-sense induction method based on pre-trained masked language models (MLMs), which can cheaply scale to large vocabularies and large corpora.", "The result is a corpus which is sense-tagged according to a corpus-derived sense inventory and where each sense is associated with indicative words.", ...
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[ "Despite recent progress in conversational question answering, most prior work does not focus on follow-up questions.", "Practical conversational question answering systems often receive follow-up questions in an ongoing conversation, and it is crucial for a system to be able to determine whether a question is a ...
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[ "Most NLP models today treat language as universal, even though socioand psycholin-gustic research shows that the communicated message is influenced by the characteristics of the speaker as well as the target audience.", "This paper surveys the landscape of personalization in natural language processing and relat...
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[ "This paper studies joint models for selecting correct answer sentences among the top k provided by answer sentence selection (AS2) modules, which are core components of retrieval-based Question Answering (QA) systems.", "Our work shows that a critical step to effectively exploiting an answer set regards modeling...
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[ "Nowadays, open-domain dialogue models can generate acceptable responses according to the historical context based on the large-scale pre-trained language models.", "However, they generally concatenate the dialogue history directly as the model input to predict the response, which we named as the flat pattern and...
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[ "Multi-document summarization (MDS) aims to compress the content in large document collections into short summaries and has important applications in story clustering for newsfeeds, presentation of search results, and timeline generation.", "However, there is a lack of datasets that realistically address such use...
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[ "Training the generative models with minimal corpus is one of the critical challenges for building open-domain dialogue systems.", "Existing methods tend to use the meta-learning framework which pre-trains the parameters on all non-target tasks then fine-tunes on the target task.", "However, fine-tuning disting...
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[ "The ability to generate clarification questions i.e., questions that identify useful missing information in a given context, is important in reducing ambiguity.", "Humans use previous experience with similar contexts to form a global view and compare it to the given context to ascertain what is missing and what ...
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