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SciEvents

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ACL
Better Character Language Modeling through Morphology
We incorporate morphological supervision into character language models (CLMs) via multitasking and show that this addition improves bits-per-character (BPC) performance across 24 languages, even when the morphology data and language modeling data are disjoint. Analyzing the CLMs shows that inflected words benefit more...
b2994e2630341e35580b4a7ff4350dbf
2,019
[ "we incorporate morphological supervision into character language models ( clms ) via multitasking and show that this addition improves bits - per - character ( bpc ) performance across 24 languages , even when the morphology data and language modeling data are disjoint .", "analyzing the clms shows that inflecte...
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ACL
Multimodal Transformer for Multimodal Machine Translation
Multimodal Machine Translation (MMT) aims to introduce information from other modality, generally static images, to improve the translation quality. Previous works propose various incorporation methods, but most of them do not consider the relative importance of multiple modalities. Equally treating all modalities may ...
454788bfec3a5eb40bdc6ff476933883
2,020
[ "multimodal machine translation ( mmt ) aims to introduce information from other modality , generally static images , to improve the translation quality .", "previous works propose various incorporation methods , but most of them do not consider the relative importance of multiple modalities .", "equally treati...
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ACL
Bootstrapped Unsupervised Sentence Representation Learning
As high-quality labeled data is scarce, unsupervised sentence representation learning has attracted much attention. In this paper, we propose a new framework with a two-branch Siamese Network which maximizes the similarity between two augmented views of each sentence. Specifically, given one augmented view of the input...
eb703dabe24459d95deabf296fc0f04d
2,021
[ "as high - quality labeled data is scarce , unsupervised sentence representation learning has attracted much attention .", "in this paper , we propose a new framework with a two - branch siamese network which maximizes the similarity between two augmented views of each sentence .", "specifically , given one aug...
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ACL
Ultra-Fine Entity Typing with Weak Supervision from a Masked Language Model
Recently, there is an effort to extend fine-grained entity typing by using a richer and ultra-fine set of types, and labeling noun phrases including pronouns and nominal nouns instead of just named entity mentions. A key challenge for this ultra-fine entity typing task is that human annotated data are extremely scarce,...
78185742947be22ebfcfe10aa1a5ee0c
2,021
[ "recently , there is an effort to extend fine - grained entity typing by using a richer and ultra - fine set of types , and labeling noun phrases including pronouns and nominal nouns instead of just named entity mentions .", "a key challenge for this ultra - fine entity typing task is that human annotated data ar...
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ACL
On the Distribution of Deep Clausal Embeddings: A Large Cross-linguistic Study
Embedding a clause inside another (“the girl [who likes cars [that run fast]] has arrived”) is a fundamental resource that has been argued to be a key driver of linguistic expressiveness. As such, it plays a central role in fundamental debates on what makes human language unique, and how they might have evolved. Empiri...
95bf4107bb85629053728ff05610337a
2,019
[ "embedding a clause inside another ( “ the girl [ who likes cars [ that run fast ] ] has arrived ” ) is a fundamental resource that has been argued to be a key driver of linguistic expressiveness .", "as such , it plays a central role in fundamental debates on what makes human language unique , and how they might...
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ACL
To Pretrain or Not to Pretrain: Examining the Benefits of Pretrainng on Resource Rich Tasks
Pretraining NLP models with variants of Masked Language Model (MLM) objectives has recently led to a significant improvements on many tasks. This paper examines the benefits of pretrained models as a function of the number of training samples used in the downstream task. On several text classification tasks, we show th...
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2,020
[ "pretraining nlp models with variants of masked language model ( mlm ) objectives has recently led to a significant improvements on many tasks .", "this paper examines the benefits of pretrained models as a function of the number of training samples used in the downstream task .", "on several text classificatio...
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ACL
Automatic ICD Coding via Interactive Shared Representation Networks with Self-distillation Mechanism
The ICD coding task aims at assigning codes of the International Classification of Diseases in clinical notes. Since manual coding is very laborious and prone to errors, many methods have been proposed for the automatic ICD coding task. However, existing works either ignore the long-tail of code frequency or the noisy ...
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2,021
[ "the icd coding task aims at assigning codes of the international classification of diseases in clinical notes .", "since manual coding is very laborious and prone to errors , many methods have been proposed for the automatic icd coding task .", "however , existing works either ignore the long - tail of code fr...
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ACL
A Pre-training Strategy for Zero-Resource Response Selection in Knowledge-Grounded Conversations
Recently, many studies are emerging towards building a retrieval-based dialogue system that is able to effectively leverage background knowledge (e.g., documents) when conversing with humans. However, it is non-trivial to collect large-scale dialogues that are naturally grounded on the background documents, which hinde...
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2,021
[ "recently , many studies are emerging towards building a retrieval - based dialogue system that is able to effectively leverage background knowledge ( e . g . , documents ) when conversing with humans .", "however , it is non - trivial to collect large - scale dialogues that are naturally grounded on the backgrou...
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ACL
Improving Compositional Generalization in Classification Tasks via Structure Annotations
Compositional generalization is the ability to generalize systematically to a new data distribution by combining known components. Although humans seem to have a great ability to generalize compositionally, state-of-the-art neural models struggle to do so. In this work, we study compositional generalization in classifi...
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2,021
[ "compositional generalization is the ability to generalize systematically to a new data distribution by combining known components .", "although humans seem to have a great ability to generalize compositionally , state - of - the - art neural models struggle to do so .", "in this work , we study compositional g...
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ACL
Learning Implicit Text Generation via Feature Matching
Generative feature matching network (GFMN) is an approach for training state-of-the-art implicit generative models for images by performing moment matching on features from pre-trained neural networks. In this paper, we present new GFMN formulations that are effective for sequential data. Our experimental results show ...
2e460351f074645178eef0ec8d5f100f
2,020
[ "generative feature matching network ( gfmn ) is an approach for training state - of - the - art implicit generative models for images by performing moment matching on features from pre - trained neural networks .", "in this paper , we present new gfmn formulations that are effective for sequential data .", "ou...
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ACL
A Generative Model for Joint Natural Language Understanding and Generation
Natural language understanding (NLU) and natural language generation (NLG) are two fundamental and related tasks in building task-oriented dialogue systems with opposite objectives: NLU tackles the transformation from natural language to formal representations, whereas NLG does the reverse. A key to success in either t...
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2,020
[ "natural language understanding ( nlu ) and natural language generation ( nlg ) are two fundamental and related tasks in building task - oriented dialogue systems with opposite objectives :", "nlu tackles the transformation from natural language to formal representations , whereas nlg does the reverse .", "a ke...
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ACL
A Copy-Augmented Generative Model for Open-Domain Question Answering
Open-domain question answering is a challenging task with a wide variety of practical applications. Existing modern approaches mostly follow a standard two-stage paradigm: retriever then reader. In this article, we focus on improving the effectiveness of the reader module and propose a novel copy-augmented generative a...
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[ "open - domain question answering is a challenging task with a wide variety of practical applications .", "existing modern approaches mostly follow a standard two - stage paradigm : retriever then reader .", "in this article , we focus on improving the effectiveness of the reader module and propose a novel copy...
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ACL
Verb Knowledge Injection for Multilingual Event Processing
Linguistic probing of pretrained Transformer-based language models (LMs) revealed that they encode a range of syntactic and semantic properties of a language. However, they are still prone to fall back on superficial cues and simple heuristics to solve downstream tasks, rather than leverage deeper linguistic informatio...
c06f24396a1045fcc3739427529401cc
2,021
[ "linguistic probing of pretrained transformer - based language models ( lms ) revealed that they encode a range of syntactic and semantic properties of a language .", "however , they are still prone to fall back on superficial cues and simple heuristics to solve downstream tasks , rather than leverage deeper ling...
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ACL
HERALD: An Annotation Efficient Method to Detect User Disengagement in Social Conversations
Open-domain dialog systems have a user-centric goal: to provide humans with an engaging conversation experience. User engagement is one of the most important metrics for evaluating open-domain dialog systems, and could also be used as real-time feedback to benefit dialog policy learning. Existing work on detecting user...
019f3ec0dce1fdc2ec1cb1c91e49bb40
2,021
[ "open - domain dialog systems have a user - centric goal : to provide humans with an engaging conversation experience .", "user engagement is one of the most important metrics for evaluating open - domain dialog systems , and could also be used as real - time feedback to benefit dialog policy learning .", "exis...
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ACL
On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation
Evaluation of cross-lingual encoders is usually performed either via zero-shot cross-lingual transfer in supervised downstream tasks or via unsupervised cross-lingual textual similarity. In this paper, we concern ourselves with reference-free machine translation (MT) evaluation where we directly compare source texts to...
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2,020
[ "evaluation of cross - lingual encoders is usually performed either via zero - shot cross - lingual transfer in supervised downstream tasks or via unsupervised cross - lingual textual similarity .", "in this paper , we concern ourselves with reference - free machine translation ( mt ) evaluation where we directly...
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ACL
Stay on the Path: Instruction Fidelity in Vision-and-Language Navigation
Advances in learning and representations have reinvigorated work that connects language to other modalities. A particularly exciting direction is Vision-and-Language Navigation(VLN), in which agents interpret natural language instructions and visual scenes to move through environments and reach goals. Despite recent pr...
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2,019
[ "advances in learning and representations have reinvigorated work that connects language to other modalities .", "a particularly exciting direction is vision - and - language navigation ( vln ) , in which agents interpret natural language instructions and visual scenes to move through environments and reach goals...
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ACL
Integrated Directional Gradients: Feature Interaction Attribution for Neural NLP Models
In this paper, we introduce Integrated Directional Gradients (IDG), a method for attributing importance scores to groups of features, indicating their relevance to the output of a neural network model for a given input. The success of Deep Neural Networks has been attributed to their ability to capture higher level fea...
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2,021
[ "in this paper , we introduce integrated directional gradients ( idg ) , a method for attributing importance scores to groups of features , indicating their relevance to the output of a neural network model for a given input .", "the success of deep neural networks has been attributed to their ability to capture ...
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ACL
BASS: Boosting Abstractive Summarization with Unified Semantic Graph
Abstractive summarization for long-document or multi-document remains challenging for the Seq2Seq architecture, as Seq2Seq is not good at analyzing long-distance relations in text. In this paper, we present BASS, a novel framework for Boosting Abstractive Summarization based on a unified Semantic graph, which aggregate...
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2,021
[ "abstractive summarization for long - document or multi - document remains challenging for the seq2seq architecture , as seq2seq is not good at analyzing long - distance relations in text .", "in this paper , we present bass , a novel framework for boosting abstractive summarization based on a unified semantic gr...
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ACL
The State and Fate of Linguistic Diversity and Inclusion in the NLP World
Language technologies contribute to promoting multilingualism and linguistic diversity around the world. However, only a very small number of the over 7000 languages of the world are represented in the rapidly evolving language technologies and applications. In this paper we look at the relation between the types of la...
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2,020
[ "language technologies contribute to promoting multilingualism and linguistic diversity around the world .", "however , only a very small number of the over 7000 languages of the world are represented in the rapidly evolving language technologies and applications .", "in this paper we look at the relation betwe...
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ACL
Uncertainty and Surprisal Jointly Deliver the Punchline: Exploiting Incongruity-Based Features for Humor Recognition
Humor recognition has been widely studied as a text classification problem using data-driven approaches. However, most existing work does not examine the actual joke mechanism to understand humor. We break down any joke into two distinct components: the set-up and the punchline, and further explore the special relation...
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2,021
[ "humor recognition has been widely studied as a text classification problem using data - driven approaches .", "however , most existing work does not examine the actual joke mechanism to understand humor .", "we break down any joke into two distinct components : the set - up and the punchline , and further expl...
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ACL
Neural Relation Extraction for Knowledge Base Enrichment
We study relation extraction for knowledge base (KB) enrichment. Specifically, we aim to extract entities and their relationships from sentences in the form of triples and map the elements of the extracted triples to an existing KB in an end-to-end manner. Previous studies focus on the extraction itself and rely on Nam...
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2,019
[ "we study relation extraction for knowledge base ( kb ) enrichment .", "specifically , we aim to extract entities and their relationships from sentences in the form of triples and map the elements of the extracted triples to an existing kb in an end - to - end manner .", "previous studies focus on the extractio...
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ACL
Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned
Multi-head self-attention is a key component of the Transformer, a state-of-the-art architecture for neural machine translation. In this work we evaluate the contribution made by individual attention heads to the overall performance of the model and analyze the roles played by them in the encoder. We find that the most...
3e4f804ce41e7e9b206687d6dc0d1980
2,019
[ "multi - head self - attention is a key component of the transformer , a state - of - the - art architecture for neural machine translation .", "in this work we evaluate the contribution made by individual attention heads to the overall performance of the model and analyze the roles played by them in the encoder ...
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ACL
Towards Learning (Dis)-Similarity of Source Code from Program Contrasts
Understanding the functional (dis)-similarity of source code is significant for code modeling tasks such as software vulnerability and code clone detection. We present DISCO (DIS-similarity of COde), a novel self-supervised model focusing on identifying (dis)similar functionalities of source code. Different from existi...
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2,022
[ "understanding the functional ( dis ) - similarity of source code is significant for code modeling tasks such as software vulnerability and code clone detection .", "we present disco ( dis - similarity of code ) , a novel self - supervised model focusing on identifying ( dis ) similar functionalities of source co...
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ACL
Multi-News: A Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Model
Automatic generation of summaries from multiple news articles is a valuable tool as the number of online publications grows rapidly. Single document summarization (SDS) systems have benefited from advances in neural encoder-decoder model thanks to the availability of large datasets. However, multi-document summarizatio...
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2,019
[ "automatic generation of summaries from multiple news articles is a valuable tool as the number of online publications grows rapidly .", "single document summarization ( sds ) systems have benefited from advances in neural encoder - decoder model thanks to the availability of large datasets .", "however , multi...
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ACL
Self-Attentive, Multi-Context One-Class Classification for Unsupervised Anomaly Detection on Text
There exist few text-specific methods for unsupervised anomaly detection, and for those that do exist, none utilize pre-trained models for distributed vector representations of words. In this paper we introduce a new anomaly detection method—Context Vector Data Description (CVDD)—which builds upon word embedding models...
46126a7a5fed03ae549d1fa8a51033ff
2,019
[ "there exist few text - specific methods for unsupervised anomaly detection , and for those that do exist , none utilize pre - trained models for distributed vector representations of words .", "in this paper we introduce a new anomaly detection method — context vector data description ( cvdd ) — which builds upo...
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ACL
Unsupervised Rewriter for Multi-Sentence Compression
Multi-sentence compression (MSC) aims to generate a grammatical but reduced compression from multiple input sentences while retaining their key information. Previous dominating approach for MSC is the extraction-based word graph approach. A few variants further leveraged lexical substitution to yield more abstractive c...
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2,019
[ "multi - sentence compression ( msc ) aims to generate a grammatical but reduced compression from multiple input sentences while retaining their key information .", "previous dominating approach for msc is the extraction - based word graph approach .", "a few variants further leveraged lexical substitution to y...
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ACL
Pretraining with Artificial Language: Studying Transferable Knowledge in Language Models
We investigate what kind of structural knowledge learned in neural network encoders is transferable to processing natural language.We design artificial languages with structural properties that mimic natural language, pretrain encoders on the data, and see how much performance the encoder exhibits on downstream tasks i...
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2,022
[ "we investigate what kind of structural knowledge learned in neural network encoders is transferable to processing natural language .", "we design artificial languages with structural properties that mimic natural language , pretrain encoders on the data , and see how much performance the encoder exhibits on down...
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ACL
Improving the Faithfulness of Attention-based Explanations with Task-specific Information for Text Classification
Neural network architectures in natural language processing often use attention mechanisms to produce probability distributions over input token representations. Attention has empirically been demonstrated to improve performance in various tasks, while its weights have been extensively used as explanations for model pr...
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2,021
[ "neural network architectures in natural language processing often use attention mechanisms to produce probability distributions over input token representations .", "attention has empirically been demonstrated to improve performance in various tasks , while its weights have been extensively used as explanations ...
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ACL
Syn-QG: Syntactic and Shallow Semantic Rules for Question Generation
Question Generation (QG) is fundamentally a simple syntactic transformation; however, many aspects of semantics influence what questions are good to form. We implement this observation by developing Syn-QG, a set of transparent syntactic rules leveraging universal dependencies, shallow semantic parsing, lexical resourc...
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2,020
[ "question generation ( qg ) is fundamentally a simple syntactic transformation ; however , many aspects of semantics influence what questions are good to form .", "we implement this observation by developing syn - qg , a set of transparent syntactic rules leveraging universal dependencies , shallow semantic parsi...
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ACL
Difficulty-Aware Machine Translation Evaluation
The high-quality translation results produced by machine translation (MT) systems still pose a huge challenge for automatic evaluation. Current MT evaluation pays the same attention to each sentence component, while the questions of real-world examinations (e.g., university examinations) have different difficulties and...
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2,021
[ "the high - quality translation results produced by machine translation ( mt ) systems still pose a huge challenge for automatic evaluation .", "current mt evaluation pays the same attention to each sentence component , while the questions of real - world examinations ( e . g . , university examinations ) have di...
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ACL
Reference Network for Neural Machine Translation
Neural Machine Translation (NMT) has achieved notable success in recent years. Such a framework usually generates translations in isolation. In contrast, human translators often refer to reference data, either rephrasing the intricate sentence fragments with common terms in source language, or just accessing to the gol...
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2,019
[ "neural machine translation ( nmt ) has achieved notable success in recent years .", "such a framework usually generates translations in isolation .", "in contrast , human translators often refer to reference data , either rephrasing the intricate sentence fragments with common terms in source language , or jus...
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ACL
Unraveling Antonym’s Word Vectors through a Siamese-like Network
Discriminating antonyms and synonyms is an important NLP task that has the difficulty that both, antonyms and synonyms, contains similar distributional information. Consequently, pairs of antonyms and synonyms may have similar word vectors. We present an approach to unravel antonymy and synonymy from word vectors based...
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2,019
[ "discriminating antonyms and synonyms is an important nlp task that has the difficulty that both , antonyms and synonyms , contains similar distributional information .", "consequently , pairs of antonyms and synonyms may have similar word vectors .", "we present an approach to unravel antonymy and synonymy fro...
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ACL
Categorizing and Inferring the Relationship between the Text and Image of Twitter Posts
Text in social media posts is frequently accompanied by images in order to provide content, supply context, or to express feelings. This paper studies how the meaning of the entire tweet is composed through the relationship between its textual content and its image. We build and release a data set of image tweets annot...
9a377af362177db713fb64ac10cbc516
2,019
[ "text in social media posts is frequently accompanied by images in order to provide content , supply context , or to express feelings .", "this paper studies how the meaning of the entire tweet is composed through the relationship between its textual content and its image .", "we build and release a data set of...
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ACL
Learning Prototypical Functions for Physical Artifacts
Humans create things for a reason. Ancient people created spears for hunting, knives for cutting meat, pots for preparing food, etc. The prototypical function of a physical artifact is a kind of commonsense knowledge that we rely on to understand natural language. For example, if someone says “She borrowed the book” th...
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ACL
Early Stopping Based on Unlabeled Samples in Text Classification
Early stopping, which is widely used to prevent overfitting, is generally based on a separate validation set. However, in low resource settings, validation-based stopping can be risky because a small validation set may not be sufficiently representative, and the reduction in the number of samples by validation split ma...
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ACL
A Statutory Article Retrieval Dataset in French
Statutory article retrieval is the task of automatically retrieving law articles relevant to a legal question. While recent advances in natural language processing have sparked considerable interest in many legal tasks, statutory article retrieval remains primarily untouched due to the scarcity of large-scale and high-...
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2,022
[ "statutory article retrieval is the task of automatically retrieving law articles relevant to a legal question .", "while recent advances in natural language processing have sparked considerable interest in many legal tasks , statutory article retrieval remains primarily untouched due to the scarcity of large - s...
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ACL
Avoiding Reasoning Shortcuts: Adversarial Evaluation, Training, and Model Development for Multi-Hop QA
Multi-hop question answering requires a model to connect multiple pieces of evidence scattered in a long context to answer the question. In this paper, we show that in the multi-hop HotpotQA (Yang et al., 2018) dataset, the examples often contain reasoning shortcuts through which models can directly locate the answer b...
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2,019
[ "multi - hop question answering requires a model to connect multiple pieces of evidence scattered in a long context to answer the question .", "in this paper , we show that in the multi - hop hotpotqa ( yang et al . , 2018 ) dataset , the examples often contain reasoning shortcuts through which models can directl...
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ACL
Meta-KD: A Meta Knowledge Distillation Framework for Language Model Compression across Domains
Pre-trained language models have been applied to various NLP tasks with considerable performance gains. However, the large model sizes, together with the long inference time, limit the deployment of such models in real-time applications. One line of model compression approaches considers knowledge distillation to disti...
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ACL
Semantic Scaffolds for Pseudocode-to-Code Generation
We propose a method for program generation based on semantic scaffolds, lightweight structures representing the high-level semantic and syntactic composition of a program. By first searching over plausible scaffolds then using these as constraints for a beam search over programs, we achieve better coverage of the searc...
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2,020
[ "we propose a method for program generation based on semantic scaffolds , lightweight structures representing the high - level semantic and syntactic composition of a program .", "by first searching over plausible scaffolds then using these as constraints for a beam search over programs , we achieve better covera...
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ACL
Self-Supervised Neural Machine Translation
We present a simple new method where an emergent NMT system is used for simultaneously selecting training data and learning internal NMT representations. This is done in a self-supervised way without parallel data, in such a way that both tasks enhance each other during training. The method is language independent, int...
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2,019
[ "we present a simple new method where an emergent nmt system is used for simultaneously selecting training data and learning internal nmt representations .", "this is done in a self - supervised way without parallel data , in such a way that both tasks enhance each other during training .", "the method is langu...
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ACL
Multilingual Molecular Representation Learning via Contrastive Pre-training
Molecular representation learning plays an essential role in cheminformatics. Recently, language model-based approaches have gained popularity as an alternative to traditional expert-designed features to encode molecules. However, these approaches only utilize a single molecular language for representation learning. Mo...
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[ "molecular representation learning plays an essential role in cheminformatics .", "recently , language model - based approaches have gained popularity as an alternative to traditional expert - designed features to encode molecules .", "however , these approaches only utilize a single molecular language for repr...
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ACL
Word Segmentation as Unsupervised Constituency Parsing
Word identification from continuous input is typically viewed as a segmentation task. Experiments with human adults suggest that familiarity with syntactic structures in their native language also influences word identification in artificial languages; however, the relation between syntactic processing and word identif...
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2,022
[ "word identification from continuous input is typically viewed as a segmentation task .", "experiments with human adults suggest that familiarity with syntactic structures in their native language also influences word identification in artificial languages ; however , the relation between syntactic processing and...
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ACL
Code-Switching Patterns Can Be an Effective Route to Improve Performance of Downstream NLP Applications: A Case Study of Humour, Sarcasm and Hate Speech Detection
In this paper, we demonstrate how code-switching patterns can be utilised to improve various downstream NLP applications. In particular, we encode various switching features to improve humour, sarcasm and hate speech detection tasks. We believe that this simple linguistic observation can also be potentially helpful in ...
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2,020
[ "in this paper , we demonstrate how code - switching patterns can be utilised to improve various downstream nlp applications .", "in particular , we encode various switching features to improve humour , sarcasm and hate speech detection tasks .", "we believe that this simple linguistic observation can also be p...
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ACL
Few-Shot Representation Learning for Out-Of-Vocabulary Words
Existing approaches for learning word embedding often assume there are sufficient occurrences for each word in the corpus, such that the representation of words can be accurately estimated from their contexts. However, in real-world scenarios, out-of-vocabulary (a.k.a. OOV) words that do not appear in training corpus e...
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2,019
[ "existing approaches for learning word embedding often assume there are sufficient occurrences for each word in the corpus , such that the representation of words can be accurately estimated from their contexts .", "however , in real - world scenarios , out - of - vocabulary ( a . k . a . oov ) words that do not ...
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ACL
Generative Pretraining for Paraphrase Evaluation
We introduce ParaBLEU, a paraphrase representation learning model and evaluation metric for text generation. Unlike previous approaches, ParaBLEU learns to understand paraphrasis using generative conditioning as a pretraining objective. ParaBLEU correlates more strongly with human judgements than existing metrics, obta...
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2,022
[ "we introduce parableu , a paraphrase representation learning model and evaluation metric for text generation .", "unlike previous approaches , parableu learns to understand paraphrasis using generative conditioning as a pretraining objective .", "parableu correlates more strongly with human judgements than exi...
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ACL
Hallucinated but Factual! Inspecting the Factuality of Hallucinations in Abstractive Summarization
State-of-the-art abstractive summarization systems often generate hallucinations; i.e., content that is not directly inferable from the source text. Despite being assumed to be incorrect, we find that much hallucinated content is actually consistent with world knowledge, which we call factual hallucinations. Including ...
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2,022
[ "state - of - the - art abstractive summarization systems often generate hallucinations ; i . e . , content that is not directly inferable from the source text .", "despite being assumed to be incorrect , we find that much hallucinated content is actually consistent with world knowledge , which we call factual ha...
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ACL
Investigating person-specific errors in chat-oriented dialogue systems
Creating chatbots to behave like real people is important in terms of believability. Errors in general chatbots and chatbots that follow a rough persona have been studied, but those in chatbots that behave like real people have not been thoroughly investigated. We collected a large amount of user interactions of a gene...
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ACL
Learning to Rank for Plausible Plausibility
Researchers illustrate improvements in contextual encoding strategies via resultant performance on a battery of shared Natural Language Understanding (NLU) tasks. Many of these tasks are of a categorical prediction variety: given a conditioning context (e.g., an NLI premise), provide a label based on an associated prom...
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2,019
[ "researchers illustrate improvements in contextual encoding strategies via resultant performance on a battery of shared natural language understanding ( nlu ) tasks .", "many of these tasks are of a categorical prediction variety : given a conditioning context ( e . g . , an nli premise ) , provide a label based ...
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ACL
Active Imitation Learning with Noisy Guidance
Imitation learning algorithms provide state-of-the-art results on many structured prediction tasks by learning near-optimal search policies. Such algorithms assume training-time access to an expert that can provide the optimal action at any queried state; unfortunately, the number of such queries is often prohibitive, ...
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2,020
[ "imitation learning algorithms provide state - of - the - art results on many structured prediction tasks by learning near - optimal search policies .", "such algorithms assume training - time access to an expert that can provide the optimal action at any queried state ; unfortunately , the number of such queries...
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ACL
Using Adversarial Attacks to Reveal the Statistical Bias in Machine Reading Comprehension Models
Pre-trained language models have achieved human-level performance on many Machine Reading Comprehension (MRC) tasks, but it remains unclear whether these models truly understand language or answer questions by exploiting statistical biases in datasets. Here, we demonstrate a simple yet effective method to attack MRC mo...
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2,021
[ "pre - trained language models have achieved human - level performance on many machine reading comprehension ( mrc ) tasks , but it remains unclear whether these models truly understand language or answer questions by exploiting statistical biases in datasets .", "here , we demonstrate a simple yet effective meth...
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ACL
Orthogonal Relation Transforms with Graph Context Modeling for Knowledge Graph Embedding
Distance-based knowledge graph embeddings have shown substantial improvement on the knowledge graph link prediction task, from TransE to the latest state-of-the-art RotatE. However, complex relations such as N-to-1, 1-to-N and N-to-N still remain challenging to predict. In this work, we propose a novel distance-based a...
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2,020
[ "distance - based knowledge graph embeddings have shown substantial improvement on the knowledge graph link prediction task , from transe to the latest state - of - the - art rotate . however , complex relations such as n - to - 1 , 1 - to - n and n - to - n still remain challenging to predict .", "in this work ,...
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ACL
Distilling Knowledge Learned in BERT for Text Generation
Large-scale pre-trained language model such as BERT has achieved great success in language understanding tasks. However, it remains an open question how to utilize BERT for language generation. In this paper, we present a novel approach, Conditional Masked Language Modeling (C-MLM), to enable the finetuning of BERT on ...
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2,020
[ "large - scale pre - trained language model such as bert has achieved great success in language understanding tasks .", "however , it remains an open question how to utilize bert for language generation .", "in this paper , we present a novel approach , conditional masked language modeling ( c - mlm ) , to enab...
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ACL
Multimodal Transformer for Unaligned Multimodal Language Sequences
Human language is often multimodal, which comprehends a mixture of natural language, facial gestures, and acoustic behaviors. However, two major challenges in modeling such multimodal human language time-series data exist: 1) inherent data non-alignment due to variable sampling rates for the sequences from each modalit...
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2,019
[ "human language is often multimodal , which comprehends a mixture of natural language , facial gestures , and acoustic behaviors .", "however , two major challenges in modeling such multimodal human language time - series data exist : 1 ) inherent data non - alignment due to variable sampling rates for the sequen...
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ACL
VALUE: Understanding Dialect Disparity in NLU
English Natural Language Understanding (NLU) systems have achieved great performances and even outperformed humans on benchmarks like GLUE and SuperGLUE. However, these benchmarks contain only textbook Standard American English (SAE). Other dialects have been largely overlooked in the NLP community. This leads to biase...
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2,022
[ "english natural language understanding ( nlu ) systems have achieved great performances and even outperformed humans on benchmarks like glue and superglue .", "however , these benchmarks contain only textbook standard american english ( sae ) .", "other dialects have been largely overlooked in the nlp communit...
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ACL
Explanation Graph Generation via Pre-trained Language Models: An Empirical Study with Contrastive Learning
Pre-trained sequence-to-sequence language models have led to widespread success in many natural language generation tasks. However, there has been relatively less work on analyzing their ability to generate structured outputs such as graphs. Unlike natural language, graphs have distinct structural and semantic properti...
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2,022
[ "pre - trained sequence - to - sequence language models have led to widespread success in many natural language generation tasks .", "however , there has been relatively less work on analyzing their ability to generate structured outputs such as graphs .", "unlike natural language , graphs have distinct structu...
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ACL
FLAT: Chinese NER Using Flat-Lattice Transformer
Recently, the character-word lattice structure has been proved to be effective for Chinese named entity recognition (NER) by incorporating the word information. However, since the lattice structure is complex and dynamic, the lattice-based models are hard to fully utilize the parallel computation of GPUs and usually ha...
259056c6c175e59a7dd315114b5e583f
2,020
[ "recently , the character - word lattice structure has been proved to be effective for chinese named entity recognition ( ner ) by incorporating the word information .", "however , since the lattice structure is complex and dynamic , the lattice - based models are hard to fully utilize the parallel computation of...
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ACL
DeSePtion: Dual Sequence Prediction and Adversarial Examples for Improved Fact-Checking
The increased focus on misinformation has spurred development of data and systems for detecting the veracity of a claim as well as retrieving authoritative evidence. The Fact Extraction and VERification (FEVER) dataset provides such a resource for evaluating endto- end fact-checking, requiring retrieval of evidence fro...
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2,020
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ACL
Integrating Semantic and Structural Information with Graph Convolutional Network for Controversy Detection
Identifying controversial posts on social media is a fundamental task for mining public sentiment, assessing the influence of events, and alleviating the polarized views. However, existing methods fail to 1) effectively incorporate the semantic information from content-related posts; 2) preserve the structural informat...
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2,020
[ "identifying controversial posts on social media is a fundamental task for mining public sentiment , assessing the influence of events , and alleviating the polarized views .", "however , existing methods fail to 1 ) effectively incorporate the semantic information from content - related posts ; 2 ) preserve the ...
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ACL
Overcoming a Theoretical Limitation of Self-Attention
Although transformers are remarkably effective for many tasks, there are some surprisingly easy-looking regular languages that they struggle with. Hahn shows that for languages where acceptance depends on a single input symbol, a transformer’s classification decisions get closer and closer to random guessing (that is, ...
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2,022
[ "although transformers are remarkably effective for many tasks , there are some surprisingly easy - looking regular languages that they struggle with .", "hahn shows that for languages where acceptance depends on a single input symbol , a transformer ’ s classification decisions get closer and closer to random gu...
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ACL
Target Inference in Argument Conclusion Generation
In argumentation, people state premises to reason towards a conclusion. The conclusion conveys a stance towards some target, such as a concept or statement. Often, the conclusion remains implicit, though, since it is self-evident in a discussion or left out for rhetorical reasons. However, the conclusion is key to unde...
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2,020
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ACL
Neural Syntactic Preordering for Controlled Paraphrase Generation
Paraphrasing natural language sentences is a multifaceted process: it might involve replacing individual words or short phrases, local rearrangement of content, or high-level restructuring like topicalization or passivization. Past approaches struggle to cover this space of paraphrase possibilities in an interpretable ...
ccdfad6a6bc09f335e9129bb1256f6c9
2,020
[ "paraphrasing natural language sentences is a multifaceted process : it might involve replacing individual words or short phrases , local rearrangement of content , or high - level restructuring like topicalization or passivization .", "past approaches struggle to cover this space of paraphrase possibilities in a...
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ACL
SimKGC: Simple Contrastive Knowledge Graph Completion with Pre-trained Language Models
Knowledge graph completion (KGC) aims to reason over known facts and infer the missing links. Text-based methods such as KGBERT (Yao et al., 2019) learn entity representations from natural language descriptions, and have the potential for inductive KGC. However, the performance of text-based methods still largely lag b...
53ff141b141332aa9869994fbdacc838
2,022
[ "knowledge graph completion ( kgc ) aims to reason over known facts and infer the missing links .", "text - based methods such as kgbert ( yao et al . , 2019 ) learn entity representations from natural language descriptions , and have the potential for inductive kgc .", "however , the performance of text - base...
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ACL
CTRLEval: An Unsupervised Reference-Free Metric for Evaluating Controlled Text Generation
Existing reference-free metrics have obvious limitations for evaluating controlled text generation models. Unsupervised metrics can only provide a task-agnostic evaluation result which correlates weakly with human judgments, whereas supervised ones may overfit task-specific data with poor generalization ability to othe...
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2,022
[ "existing reference - free metrics have obvious limitations for evaluating controlled text generation models .", "unsupervised metrics can only provide a task - agnostic evaluation result which correlates weakly with human judgments , whereas supervised ones may overfit task - specific data with poor generalizati...
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ACL
Knowledge Supports Visual Language Grounding: A Case Study on Colour Terms
In human cognition, world knowledge supports the perception of object colours: knowing that trees are typically green helps to perceive their colour in certain contexts. We go beyond previous studies on colour terms using isolated colour swatches and study visual grounding of colour terms in realistic objects. Our mode...
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2,020
[ "in human cognition , world knowledge supports the perception of object colours : knowing that trees are typically green helps to perceive their colour in certain contexts .", "we go beyond previous studies on colour terms using isolated colour swatches and study visual grounding of colour terms in realistic obje...
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ACL
LGESQL: Line Graph Enhanced Text-to-SQL Model with Mixed Local and Non-Local Relations
This work aims to tackle the challenging heterogeneous graph encoding problem in the text-to-SQL task. Previous methods are typically node-centric and merely utilize different weight matrices to parameterize edge types, which 1) ignore the rich semantics embedded in the topological structure of edges, and 2) fail to di...
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ACL
Unsupervised Opinion Summarization as Copycat-Review Generation
Opinion summarization is the task of automatically creating summaries that reflect subjective information expressed in multiple documents, such as product reviews. While the majority of previous work has focused on the extractive setting, i.e., selecting fragments from input reviews to produce a summary, we let the mod...
968998b12a7445632e848f26552f25bc
2,020
[ "opinion summarization is the task of automatically creating summaries that reflect subjective information expressed in multiple documents , such as product reviews .", "while the majority of previous work has focused on the extractive setting , i . e . , selecting fragments from input reviews to produce a summar...
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ACL
A Unified Generative Framework for Aspect-based Sentiment Analysis
Aspect-based Sentiment Analysis (ABSA) aims to identify the aspect terms, their corresponding sentiment polarities, and the opinion terms. There exist seven subtasks in ABSA. Most studies only focus on the subsets of these subtasks, which leads to various complicated ABSA models while hard to solve these subtasks in a ...
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2,021
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ACL
FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding
The few-shot natural language understanding (NLU) task has attracted much recent attention. However, prior methods have been evaluated under a disparate set of protocols, which hinders fair comparison and measuring the progress of the field. To address this issue, we introduce an evaluation framework that improves prev...
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2,022
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ACL
MultiMET: A Multimodal Dataset for Metaphor Understanding
Metaphor involves not only a linguistic phenomenon, but also a cognitive phenomenon structuring human thought, which makes understanding it challenging. As a means of cognition, metaphor is rendered by more than texts alone, and multimodal information in which vision/audio content is integrated with the text can play a...
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2,021
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ACL
Perturbed Masking: Parameter-free Probing for Analyzing and Interpreting BERT
By introducing a small set of additional parameters, a probe learns to solve specific linguistic tasks (e.g., dependency parsing) in a supervised manner using feature representations (e.g., contextualized embeddings). The effectiveness of such probing tasks is taken as evidence that the pre-trained model encodes lingui...
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ACL
BanditMTL: Bandit-based Multi-task Learning for Text Classification
Task variance regularization, which can be used to improve the generalization of Multi-task Learning (MTL) models, remains unexplored in multi-task text classification. Accordingly, to fill this gap, this paper investigates how the task might be effectively regularized, and consequently proposes a multi-task learning m...
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ACL
TwittIrish: A Universal Dependencies Treebank of Tweets in Modern Irish
Modern Irish is a minority language lacking sufficient computational resources for the task of accurate automatic syntactic parsing of user-generated content such as tweets. Although language technology for the Irish language has been developing in recent years, these tools tend to perform poorly on user-generated cont...
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2,022
[ "modern irish is a minority language lacking sufficient computational resources for the task of accurate automatic syntactic parsing of user - generated content such as tweets .", "although language technology for the irish language has been developing in recent years , these tools tend to perform poorly on user ...
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ACL
Topic Sensitive Attention on Generic Corpora Corrects Sense Bias in Pretrained Embeddings
Given a small corpus D_T pertaining to a limited set of focused topics, our goal is to train embeddings that accurately capture the sense of words in the topic in spite of the limited size of D_T. These embeddings may be used in various tasks involving D_T. A popular strategy in limited data settings is to adapt pretra...
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2,019
[ "given a small corpus d _ t pertaining to a limited set of focused topics , our goal is to train embeddings that accurately capture the sense of words in the topic in spite of the limited size of d _ t . these embeddings may be used in various tasks involving d _ t . a popular strategy in limited data settings is t...
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ACL
Towards Unsupervised Text Classification Leveraging Experts and Word Embeddings
Text classification aims at mapping documents into a set of predefined categories. Supervised machine learning models have shown great success in this area but they require a large number of labeled documents to reach adequate accuracy. This is particularly true when the number of target categories is in the tens or th...
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2,019
[ "text classification aims at mapping documents into a set of predefined categories .", "supervised machine learning models have shown great success in this area but they require a large number of labeled documents to reach adequate accuracy .", "this is particularly true when the number of target categories is ...
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ACL
Observing Dialogue in Therapy: Categorizing and Forecasting Behavioral Codes
Automatically analyzing dialogue can help understand and guide behavior in domains such as counseling, where interactions are largely mediated by conversation. In this paper, we study modeling behavioral codes used to asses a psychotherapy treatment style called Motivational Interviewing (MI), which is effective for ad...
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2,019
[ "automatically analyzing dialogue can help understand and guide behavior in domains such as counseling , where interactions are largely mediated by conversation .", "in this paper , we study modeling behavioral codes used to asses a psychotherapy treatment style called motivational interviewing ( mi ) , which is ...
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ACL
DeFormer: Decomposing Pre-trained Transformers for Faster Question Answering
Transformer-based QA models use input-wide self-attention – i.e. across both the question and the input passage – at all layers, causing them to be slow and memory-intensive. It turns out that we can get by without input-wide self-attention at all layers, especially in the lower layers. We introduce DeFormer, a decompo...
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2,020
[ "transformer - based qa models use input - wide self - attention – i . e . across both the question and the input passage – at all layers , causing them to be slow and memory - intensive .", "it turns out that we can get by without input - wide self - attention at all layers , especially in the lower layers .", ...
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ACL
Sparse Sequence-to-Sequence Models
Sequence-to-sequence models are a powerful workhorse of NLP. Most variants employ a softmax transformation in both their attention mechanism and output layer, leading to dense alignments and strictly positive output probabilities. This density is wasteful, making models less interpretable and assigning probability mass...
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2,019
[ "sequence - to - sequence models are a powerful workhorse of nlp .", "most variants employ a softmax transformation in both their attention mechanism and output layer , leading to dense alignments and strictly positive output probabilities .", "this density is wasteful , making models less interpretable and ass...
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ACL
Investigating label suggestions for opinion mining in German Covid-19 social media
This work investigates the use of interactively updated label suggestions to improve upon the efficiency of gathering annotations on the task of opinion mining in German Covid-19 social media data. We develop guidelines to conduct a controlled annotation study with social science students and find that suggestions from...
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2,021
[ "this work investigates the use of interactively updated label suggestions to improve upon the efficiency of gathering annotations on the task of opinion mining in german covid - 19 social media data .", "we develop guidelines to conduct a controlled annotation study with social science students and find that sug...
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ACL
Robust Encodings: A Framework for Combating Adversarial Typos
Despite excellent performance on many tasks, NLP systems are easily fooled by small adversarial perturbations of inputs. Existing procedures to defend against such perturbations are either (i) heuristic in nature and susceptible to stronger attacks or (ii) provide guaranteed robustness to worst-case attacks, but are in...
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2,020
[ "despite excellent performance on many tasks , nlp systems are easily fooled by small adversarial perturbations of inputs .", "existing procedures to defend against such perturbations are either ( i ) heuristic in nature and susceptible to stronger attacks or ( ii ) provide guaranteed robustness to worst - case a...
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ACL
Reasoning with Multimodal Sarcastic Tweets via Modeling Cross-Modality Contrast and Semantic Association
Sarcasm is a sophisticated linguistic phenomenon to express the opposite of what one really means. With the rapid growth of social media, multimodal sarcastic tweets are widely posted on various social platforms. In multimodal context, sarcasm is no longer a pure linguistic phenomenon, and due to the nature of social m...
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2,020
[ "sarcasm is a sophisticated linguistic phenomenon to express the opposite of what one really means .", "with the rapid growth of social media , multimodal sarcastic tweets are widely posted on various social platforms .", "in multimodal context , sarcasm is no longer a pure linguistic phenomenon , and due to th...
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ACL
Evidence-Aware Inferential Text Generation with Vector Quantised Variational AutoEncoder
Generating inferential texts about an event in different perspectives requires reasoning over different contexts that the event occurs. Existing works usually ignore the context that is not explicitly provided, resulting in a context-independent semantic representation that struggles to support the generation. To addre...
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2,020
[ "generating inferential texts about an event in different perspectives requires reasoning over different contexts that the event occurs .", "existing works usually ignore the context that is not explicitly provided , resulting in a context - independent semantic representation that struggles to support the genera...
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ACL
Pyramid-BERT: Reducing Complexity via Successive Core-set based Token Selection
Transformer-based language models such as BERT (CITATION) have achieved the state-of-the-art performance on various NLP tasks, but are computationally prohibitive. A recent line of works use various heuristics to successively shorten sequence length while transforming tokens through encoders, in tasks such as classific...
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2,022
[ "transformer - based language models such as bert ( citation ) have achieved the state - of - the - art performance on various nlp tasks , but are computationally prohibitive .", "a recent line of works use various heuristics to successively shorten sequence length while transforming tokens through encoders , in ...
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ACL
Canary Extraction in Natural Language Understanding Models
Natural Language Understanding (NLU) models can be trained on sensitive information such as phone numbers, zip-codes etc. Recent literature has focused on Model Inversion Attacks (ModIvA) that can extract training data from model parameters. In this work, we present a version of such an attack by extracting canaries in...
261b7b57df45ec16063e59d95482e714
2,022
[ "natural language understanding ( nlu ) models can be trained on sensitive information such as phone numbers , zip - codes etc .", "recent literature has focused on model inversion attacks ( modiva ) that can extract training data from model parameters .", "in this work , we present a version of such an attack ...
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ACL
Label-Agnostic Sequence Labeling by Copying Nearest Neighbors
Retrieve-and-edit based approaches to structured prediction, where structures associated with retrieved neighbors are edited to form new structures, have recently attracted increased interest. However, much recent work merely conditions on retrieved structures (e.g., in a sequence-to-sequence framework), rather than ex...
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2,019
[ "retrieve - and - edit based approaches to structured prediction , where structures associated with retrieved neighbors are edited to form new structures , have recently attracted increased interest .", "however , much recent work merely conditions on retrieved structures ( e . g . , in a sequence - to - sequence...
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ACL
Using Meta-Knowledge Mined from Identifiers to Improve Intent Recognition in Conversational Systems
In this paper we explore the improvement of intent recognition in conversational systems by the use of meta-knowledge embedded in intent identifiers. Developers often include such knowledge, structure as taxonomies, in the documentation of chatbots. By using neuro-symbolic algorithms to incorporate those taxonomies int...
24c097131183fec9bb7f8616b5acc8c9
2,021
[ "in this paper we explore the improvement of intent recognition in conversational systems by the use of meta - knowledge embedded in intent identifiers .", "developers often include such knowledge , structure as taxonomies , in the documentation of chatbots .", "by using neuro - symbolic algorithms to incorpora...
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ACL
Span-based Localizing Network for Natural Language Video Localization
Given an untrimmed video and a text query, natural language video localization (NLVL) is to locate a matching span from the video that semantically corresponds to the query. Existing solutions formulate NLVL either as a ranking task and apply multimodal matching architecture, or as a regression task to directly regress...
573cf38b1fae55e704630915bbd0910d
2,020
[ "given an untrimmed video and a text query , natural language video localization ( nlvl ) is to locate a matching span from the video that semantically corresponds to the query .", "existing solutions formulate nlvl either as a ranking task and apply multimodal matching architecture , or as a regression task to d...
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ACL
[CASPI] Causal-aware Safe Policy Improvement for Task-oriented Dialogue
The recent success of reinforcement learning (RL) in solving complex tasks is often attributed to its capacity to explore and exploit an environment.Sample efficiency is usually not an issue for tasks with cheap simulators to sample data online.On the other hand, Task-oriented Dialogues (ToD) are usually learnt from of...
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[ "the recent success of reinforcement learning ( rl ) in solving complex tasks is often attributed to its capacity to explore and exploit an environment .", "sample efficiency is usually not an issue for tasks with cheap simulators to sample data online .", "on the other hand , task - oriented dialogues ( tod ) ...
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ACL
Label Semantic Aware Pre-training for Few-shot Text Classification
In text classification tasks, useful information is encoded in the label names. Label semantic aware systems have leveraged this information for improved text classification performance during fine-tuning and prediction. However, use of label-semantics during pre-training has not been extensively explored. We therefore...
93a1485fec33a43a2c5fb64a4dc0b65b
2,022
[ "in text classification tasks , useful information is encoded in the label names .", "label semantic aware systems have leveraged this information for improved text classification performance during fine - tuning and prediction .", "however , use of label - semantics during pre - training has not been extensive...
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ACL
Multi-Scale Progressive Attention Network for Video Question Answering
Understanding the multi-scale visual information in a video is essential for Video Question Answering (VideoQA). Therefore, we propose a novel Multi-Scale Progressive Attention Network (MSPAN) to achieve relational reasoning between cross-scale video information. We construct clips of different lengths to represent dif...
94c8873abaf7fa8f5598b1ccca4b45bc
2,021
[ "understanding the multi - scale visual information in a video is essential for video question answering ( videoqa ) .", "therefore , we propose a novel multi - scale progressive attention network ( mspan ) to achieve relational reasoning between cross - scale video information .", "we construct clips of differ...
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ACL
GWLAN: General Word-Level AutocompletioN for Computer-Aided Translation
Computer-aided translation (CAT), the use of software to assist a human translator in the translation process, has been proven to be useful in enhancing the productivity of human translators. Autocompletion, which suggests translation results according to the text pieces provided by human translators, is a core functio...
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2,021
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ACL
Keep It Simple: Unsupervised Simplification of Multi-Paragraph Text
This work presents Keep it Simple (KiS), a new approach to unsupervised text simplification which learns to balance a reward across three properties: fluency, salience and simplicity. We train the model with a novel algorithm to optimize the reward (k-SCST), in which the model proposes several candidate simplifications...
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2,021
[ "this work presents keep it simple ( kis ) , a new approach to unsupervised text simplification which learns to balance a reward across three properties : fluency , salience and simplicity .", "we train the model with a novel algorithm to optimize the reward ( k - scst ) , in which the model proposes several cand...
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ACL
Improving Paraphrase Detection with the Adversarial Paraphrasing Task
If two sentences have the same meaning, it should follow that they are equivalent in their inferential properties, i.e., each sentence should textually entail the other. However, many paraphrase datasets currently in widespread use rely on a sense of paraphrase based on word overlap and syntax. Can we teach them instea...
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2,021
[ "if two sentences have the same meaning , it should follow that they are equivalent in their inferential properties , i . e . , each sentence should textually entail the other .", "however , many paraphrase datasets currently in widespread use rely on a sense of paraphrase based on word overlap and syntax .", "...
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ACL
Improving Formality Style Transfer with Context-Aware Rule Injection
Models pre-trained on large-scale regular text corpora often do not work well for user-generated data where the language styles differ significantly from the mainstream text. Here we present Context-Aware Rule Injection (CARI), an innovative method for formality style transfer (FST) by injecting multiple rules into an ...
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2,021
[ "models pre - trained on large - scale regular text corpora often do not work well for user - generated data where the language styles differ significantly from the mainstream text .", "here we present context - aware rule injection ( cari ) , an innovative method for formality style transfer ( fst ) by injecting...
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ACL
Multilingual Detection of Personal Employment Status on Twitter
Detecting disclosures of individuals’ employment status on social media can provide valuable information to match job seekers with suitable vacancies, offer social protection, or measure labor market flows. However, identifying such personal disclosures is a challenging task due to their rarity in a sea of social media...
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2,022
[ "detecting disclosures of individuals ’ employment status on social media can provide valuable information to match job seekers with suitable vacancies , offer social protection , or measure labor market flows .", "however , identifying such personal disclosures is a challenging task due to their rarity in a sea ...
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ACL
GoEmotions: A Dataset of Fine-Grained Emotions
Understanding emotion expressed in language has a wide range of applications, from building empathetic chatbots to detecting harmful online behavior. Advancement in this area can be improved using large-scale datasets with a fine-grained typology, adaptable to multiple downstream tasks. We introduce GoEmotions, the lar...
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2,020
[ "understanding emotion expressed in language has a wide range of applications , from building empathetic chatbots to detecting harmful online behavior .", "advancement in this area can be improved using large - scale datasets with a fine - grained typology , adaptable to multiple downstream tasks .", "we introd...
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ACL
Cross-modal Coherence Modeling for Caption Generation
We use coherence relations inspired by computational models of discourse to study the information needs and goals of image captioning. Using an annotation protocol specifically devised for capturing image–caption coherence relations, we annotate 10,000 instances from publicly-available image–caption pairs. We introduce...
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2,020
[ "we use coherence relations inspired by computational models of discourse to study the information needs and goals of image captioning .", "using an annotation protocol specifically devised for capturing image – caption coherence relations , we annotate 10 , 000 instances from publicly - available image – caption...
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ACL
Parallel Instance Query Network for Named Entity Recognition
Named entity recognition (NER) is a fundamental task in natural language processing. Recent works treat named entity recognition as a reading comprehension task, constructing type-specific queries manually to extract entities. This paradigm suffers from three issues. First, type-specific queries can only extract one ty...
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2,022
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ACL
Matching Article Pairs with Graphical Decomposition and Convolutions
Identifying the relationship between two articles, e.g., whether two articles published from different sources describe the same breaking news, is critical to many document understanding tasks. Existing approaches for modeling and matching sentence pairs do not perform well in matching longer documents, which embody mo...
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2,019
[ "identifying the relationship between two articles , e . g . , whether two articles published from different sources describe the same breaking news , is critical to many document understanding tasks .", "existing approaches for modeling and matching sentence pairs do not perform well in matching longer documents...
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ACL
A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters
Few-shot crosslingual transfer has been shown to outperform its zero-shot counterpart with pretrained encoders like multilingual BERT. Despite its growing popularity, little to no attention has been paid to standardizing and analyzing the design of few-shot experiments. In this work, we highlight a fundamental risk pos...
da54b8816f0e2663b57a673fb4570084
2,021
[ "few - shot crosslingual transfer has been shown to outperform its zero - shot counterpart with pretrained encoders like multilingual bert .", "despite its growing popularity , little to no attention has been paid to standardizing and analyzing the design of few - shot experiments .", "in this work , we highlig...
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ACL
Analysing Lexical Semantic Change with Contextualised Word Representations
This paper presents the first unsupervised approach to lexical semantic change that makes use of contextualised word representations. We propose a novel method that exploits the BERT neural language model to obtain representations of word usages, clusters these representations into usage types, and measures change alon...
ff630d2b6923feb578b232cfe9f548db
2,020
[ "this paper presents the first unsupervised approach to lexical semantic change that makes use of contextualised word representations .", "we propose a novel method that exploits the bert neural language model to obtain representations of word usages , clusters these representations into usage types , and measure...
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