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naacl_data_prog

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[ "In this paper we apply self-knowledge distillation to text summarization which we argue can alleviate problems with maximum-likelihood training on single reference and noisy datasets.", "Instead of relying on one-hot annotation labels, our student summarization model is trained with guidance from a teacher which...
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[ "Prerequisite relations among concepts are crucial for educational applications, such as curriculum planning and intelligent tutoring.", "In this paper, we propose a novel concept prerequisite relation learning approach, named CPRL, which combines both concept representation learned from a heterogeneous graph and...
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[ "Contextualized representations (e.g. ELMo, BERT) have become the default pretrained representations for downstream NLP applications.", "In some settings, this transition has rendered their static embedding predecessors (e.g. Word2Vec, GloVe) obsolete.", "As a side-effect, we observe that older interpretability...
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[ "Related tasks often have inter-dependence on each other and perform better when solved in a joint framework.", "In this paper, we present a deep multi-task learning framework that jointly performs sentiment and emotion analysis both.", "The multi-modal inputs (i.e., text , acoustic and visual frames ) of a vid...
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[ "Abstract Deep learning (DL) techniques involving fine-tuning large numbers of model parameters have delivered impressive performance on the task of discriminating between language produced by cognitively healthy individuals, and those with Alzheimer's disease (AD).", "However, questions remain about their abilit...
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[ "This paper presents the first large-scale meta-evaluation of machine translation (MT).", "We annotated MT evaluations conducted in 769 research papers published from 2010 to 2020.", "Our study shows that practices for automatic MT evaluation have dramatically changed during the past decade and follow concernin...
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[ "This paper presents the problem of conversational plotting agents that carry out plotting actions from natural language instructions.", "To facilitate the development of such agents, we introduce CHARTDIALOGS , a new multi-turn dialog dataset, covering a popular plotting library, matplotlib .", "The dataset co...
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[ "Recently, many works have tried to augment the performance of Chinese named entity recognition (NER) using word lexicons.", "As a representative, Lattice-LSTM (Zhang and Yang, 2018) has achieved new benchmark results on several public Chinese NER datasets.", "However, Lattice-LSTM has a complex model architect...
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[ "We present a new dataset comprised of 210,532 tokens evenly drawn from 100 different English-language literary texts annotated for ACE entity categories (person, location, geo-political entity, facility, organization, and vehicle).", "These categories include non-named entities (such as the boy, the kitchen) and...
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[ "In Neural Machine Translation (and, more generally, conditional language modeling), the generation of a target token is influenced by two types of context: the source and the prefix of the target sequence.", "While many attempts to understand the internal workings of NMT models have been made, none of them expli...
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[ "Neural architectures are the current state of the art in Word Sense Disambiguation (WSD).", "However, they make limited use of the vast amount of relational information encoded in Lexical Knowledge Bases (LKB).", "We present Enhanced WSD Integrating Synset Embeddings and Relations (EWISER), a neural supervised...
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[ "Conversational context information, higher-level knowledge that spans across sentences, can help to recognize a long conversation.", "However, existing speech recognition models are typically built at a sentence level, and thus it may not capture important conversational context information.", "The recent prog...
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[ "Zhiwen Xie 1 , Guangyou Zhou 2 , Jin Liu 1 , Jimmy Xiangji Huang 3 1 School of Computer Science, Wuhan University 2 School of Computer Science, Central China Normal University 3 School of Information Technology, York University xiezhiwen@whu.edu.cn , gyzhou@mail.ccnu.edu.cn jinliu@whu.edu.cn , jhuang@yorku.ca", ...
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[ "Recent Transformer-based architectures, e.g., BERT, provide impressive results in many Natural Language Processing tasks.", "However, most of the adopted benchmarks are made of (sometimes hundreds of) thousands of examples.", "In many real scenarios, obtaining high-quality annotated data is expensive and time-...
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[ "We explore the problem of audio captioning 1 : generating natural language description for any kind of audio in the wild, which has been surprisingly unexplored in previous research.", "We contribute a large-scale dataset of 46K audio clips with human-written text pairs collected via crowdsourcing on the AudioSe...
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[ "Open Information Extraction ( OPENIE ) extracts meaningful structured tuples from freeform text.", "Most previous work on OPENIE considers extracting data from one sentence at a time.", "We describe NEURON , a system for extracting tuples from question-answer pairs.", "Since real questions and answers often ...
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[ "We propose a self-supervised method to solve Pronoun Disambiguation and Winograd Schema Challenge problems.", "Our approach exploits the characteristic structure of training corpora related to so-called trigger words, which are responsible for flipping the answer in pronoun disambiguation.", "We achieve such c...
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[ "Cornell University llee@cs.cornell.edu", "Abstract", "Naturally-occurring bracketings, such as answer fragments to natural language questions and hyperlinks on webpages, can reflect human syntactic intuition regarding phrasal boundaries.", "Their availability and approximate correspondence to syntax make the...
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[ "Natural Questions is a new challenging machine reading comprehension benchmark with two-grained answers, which are a long answer (typically a paragraph) and a short answer (one or more entities inside the long answer).", "Despite the effectiveness of existing methods on this benchmark, they treat these two sub-t...
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[ "While pretrained language models achieve excellent performance on natural language understanding benchmarks, they tend to rely on spurious correlations and generalize poorly to out-of-distribution (OOD) data.", "Recent work has explored using counterfactually-augmented data (CAD)data generated by minimally pertu...
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[ "Multi-label text classification is one of the fundamental tasks in natural language processing.", "Previous studies have difficulties to distinguish similar labels well because they learn the same document representations for different labels, that is they do not explicitly extract label-specific semantic compon...
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[ "While neural dependency parsers provide state-of-the-art accuracy for several languages, they still rely on large amounts of costly labeled training data.", "We demonstrate that in the small data regime, where uncertainty around parameter estimation and model prediction matters the most, Bayesian neural modeling...
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[ "Few-shot learning has drawn researchers' attention to overcome the problem of data scarcity.", "Recently, large pre-trained language models have shown great performance in few-shot learning for various downstream tasks, such as question answering and machine translation.", "Nevertheless, little exploration has...
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[ "The automatic detection of satire vs. regular news is relevant for downstream applications (for instance, knowledge base population) and to improve the understanding of linguistic characteristics of satire.", "Recent approaches build upon corpora which have been labeled automatically based on article sources.", ...
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[ "Existing Natural Language Inference (NLI) datasets, while being instrumental in the advancement of Natural Language Understanding (NLU) research, are not related to scientific text.", "In this paper, we introduce SCINLI, a large dataset for NLI that captures the formality in scientific text and contains 107 , 41...
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[ "Unsupervised machine translation (MT) has recently achieved impressive results with monolingual corpora only.", "However, it is still challenging to associate source-target sentences in the latent space.", "As people speak different languages biologically share similar visual systems, the potential of achievin...
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[ "Beam search optimization (Wiseman and Rush, 2016) resolves many issues in neural machine translation.", "However, this method lacks principled stopping criteria and does not learn how to stop during training, and the model naturally prefers longer hypotheses during the testing time in practice since they use the...
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[ "We present an effective end-to-end memory network model that jointly ( i ) predicts whether a given document can be considered as relevant evidence for a given claim, and ( ii ) extracts snippets of evidence that can be used to reason about the factuality of the target claim.", "Our model combines the advantages...
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[ "Igor Malioutov Bloomberg L.P. imalioutov@bloomberg.net", "Abstract", "While the predictive performance of modern statistical dependency parsers relies heavily on the availability of expensive expert-annotated treebank data, not all annotations contribute equally to the training of the parsers.", "In this pap...
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[ "We present a new neural model for text summarization that first extracts sentences from a document and then compresses them.", "The proposed model offers a balance that sidesteps the difficulties in abstractive methods while generating more concise summaries than extractive methods.", "In addition, our model d...
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[ "Generating fluent and informative responses is of critical importance for task-oriented dialogue systems.", "Existing pipeline approaches generally predict multiple dialogue acts first and use them to assist response generation.", "There are at least two shortcomings with such approaches.", "First, the inher...
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[ "Contextual string embeddings are a recent type of contextualized word embedding that were shown to yield state-of-the-art results when utilized in a range of sequence labeling tasks.", "They are based on character-level language models which treat text as distributions over characters and are capable of generati...
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[ "Humans use language to refer to entities in the external world.", "Motivated by this, in recent years several models that incorporate a bias towards learning entity representations have been proposed.", "Such entity-centric models have shown empirical success, but we still know little about why.", "In this p...
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[ "In data-to-text (D2T) generation, training on in-domain data leads to overfitting to the data representation and repeating training data noise.", "We examine how to avoid finetuning pretrained language models (PLMs) on D2T generation datasets while still taking advantage of surface realization capabilities of PL...
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[ "The uncertainty measurement of classifiers' predictions is especially important in applications such as medical diagnoses that need to ensure limited human resources can focus on the most uncertain predictions returned by machine learning models.", "However, few existing uncertainty models attempt to improve ove...
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[ "We propose a new model for speaker naming in movies that leverages visual, textual, and acoustic modalities in an unified optimization framework.", "To evaluate the performance of our model, we introduce a new dataset consisting of six episodes of the Big Bang Theory TV show and eighteen full movies covering dif...
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[ "Attention mechanisms have seen wide adoption in neural NLP models.", "In addition to improving predictive performance, these are often touted as affording transparency: models equipped with attention provide a distribution over attended-to input units, and this is often presented (at least implicitly) as communi...
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[ "The choice of negative examples is important in noise contrastive estimation.", "Recent works find that hard negativeshighest-scoring incorrect examples under the modelare effective in practice, but they are used without a formal justification.", "We develop analytical tools to understand the role of hard nega...
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[ "Pre-trained language models like BERT are performant in a wide range of natural language tasks.", "However, they are resource exhaustive and computationally expensive for industrial scenarios.", "Thus, early exits are adopted at each layer of BERT to perform adaptive computation by predicting easier samples wi...
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[ "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 ...
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[ "Suppose we want to specify the inductive bias that married couples typically go on honeymoons for the task of extracting pairs of spouses from text.", "In this paper, we allow model developers to specify these types of inductive biases as natural language explanations.", "We use BERT fine-tuned on MultiNLI to ...
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[ "Most existing joint neural models for Information Extraction (IE) use local task-specific classifiers to predict labels for individual instances (e.g., trigger, relation) regardless of their interactions.", "For example, a VICTIM of a DIE event is likely to be a VICTIM of an ATTACK event in the same sentence.", ...
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[ "Style transfer has been widely explored in natural language generation with non-parallel corpus by directly or indirectly extracting a notion of style from source and target domain corpus.", "A common shortcoming of existing approaches is the prerequisite of joint annotations across all the stylistic dimensions ...
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[ "Open-domain code generation aims to generate code in a general-purpose programming language (such as Python) from natural language (NL) intents.", "Motivated by the intuition that developers usually retrieve resources on the web when writing code, we explore the effectiveness of incorporating two varieties of ex...
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[ "Text-based games provide an interactive way to study natural language processing.", "While deep reinforcement learning has shown effectiveness in developing the game playing agent, the low sample efficiency and the large action space remain to be the two major challenges that hinder the DRL from being applied in...
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[ "We introduce MeSys , a meaning-based approach, for solving English math word problems (MWPs) via understanding and reasoning in this paper.", "It first analyzes the text, transforms both body and question parts into their corresponding logic forms, and then performs inference on them.", "The associated context...
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[ "Large transformer-based language models have been shown to be very effective in many classification tasks.", "However, their computational complexity prevents their use in applications requiring the classification of a large set of candidates.", "While previous works have investigated approaches to reduce mode...
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[ "The recent GPT-3 model (Brown et al., 2020) achieves remarkable few-shot performance solely by leveraging a natural-language prompt and a few task demonstrations as input context.", "Inspired by their findings, we study few-shot learning in a more practical scenario, where we use smaller language models for whic...
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[ "Most recent approaches use the sequence-to-sequence model for paraphrase generation.", "The existing sequence-to-sequence model tends to memorize the words and the patterns in the training dataset instead of learning the meaning of the words.", "Therefore, the generated sentences are often grammatically correc...
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[ "We propose a novel transition-based algorithm that straightforwardly parses sentences from left to right by building n attachments, with n being the length of the input sentence.", "Similarly to the recent stack-pointer parser by Ma et al. (2018), we use the pointer network framework that, given a word, can dire...
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[ "In this paper, we propose I nverse A dversarial T raining (IAT) algorithm for training neural dialogue systems to avoid generic responses and model dialogue history better.", "In contrast to standard adversarial training algorithms, IAT encourages the model to be sensitive to the perturbation in the dialogue his...
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[ "Neural discrete reasoning (NDR) has shown remarkable progress in combining deep models with discrete reasoning.", "However, we find that existing NDR solution suffers from large performance drop on hypothetical questions, e.g., what the annualized rate of return would be if the revenue in 2020 was doubled .", ...
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[ "End-to-end models for speech translation (ST) more tightly couple speech recognition (ASR) and machine translation (MT) than a traditional cascade of separate ASR and MT models, with simpler model architectures and the potential for reduced error propagation.", "Their performance is often assumed to be superior,...
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[ "While there is a large amount of research in the field of Lexical Semantic Change Detection, only few approaches go beyond a standard benchmark evaluation of existing models.", "In this paper, we propose a shift of focus from change detection to change discovery, i.e., discovering novel word senses over time fro...
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[ "Multilingual pre-trained models are able to zero-shot transfer knowledge from rich-resource to low-resource languages in machine reading comprehension (MRC).", "However, inherent linguistic discrepancies in different languages could make answer spans predicted by zero-shot transfer violate syntactic constraints ...
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[ "Distributional semantic models have become a mainstay in NLP, providing useful features for downstream tasks.", "However, assessing long-term progress requires explicit long-term goals.", "In this paper, I take a broad linguistic perspective, looking at how well current models can deal with various semantic ch...
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[ "We propose a novel manifold based geometric approach for learning unsupervised alignment of word embeddings between the source and the target languages.", "Our approach formulates the alignment learning problem as a domain adaptation problem over the manifold of doubly stochastic matrices.", "This viewpoint ar...
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[ "The long short-term memory (LSTM) language model (LM) has been widely investigated for automatic speech recognition (ASR) and natural language processing (NLP).", "Although excellent performance is obtained for large vocabulary tasks, tremendous memory consumption prohibits the use of LSTM LMs in low-resource de...
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[ "To effectively apply robots in working environments and assist humans, it is essential to develop and evaluate how visual grounding (VG) can affect machine performance on occluded objects.", "However, current VG works are limited in working environments, such as offices and warehouses, where objects are usually ...
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[ "Inflecting When There's No Majority: Limitations of Encoder-Decoder Neural Networks as Cognitive Models for German Plurals Kate McCurdy Sharon Goldwater Adam Lopez Institute for Language, Cognition and Computation School of Informatics University of Edinburgh kate.mccurdy@ed.ac.uk, { sgwater, alopez } @inf.ed.ac.u...
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[ "Predicting reading time has been a subject of much previous work, focusing on how different words affect human processing, measured by reading time.", "However, previous work has dealt with a limited number of participants as well as word level only predictions (i.e. predicting the time to read a single word).",...
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[ "Modern neural machine translation (NMT) models have achieved competitive performance in standard benchmarks such as WMT.", "However, there still exist significant issues such as robustness, domain generalization, etc.", "In this paper, we study NMT models from the perspective of compositional generalization by...
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[ "Languages are continuously undergoing changes, and the mechanisms that underlie these changes are still a matter of debate.", "In this work, we approach language evolution through the lens of causality in order to model not only how various distributional factors associate with language change, but how they caus...
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[ "Recent studies have shown the advantages of evaluating NLG systems using pairwise comparisons as opposed to direct assessment.", "Given k systems, a naive approach for identifying the top-ranked system would be to uniformly obtain pairwise comparisons from all (cid:0) k 2 (cid:1) pairs of systems.", "However, ...
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[ "Unsupervised domain adaptation (UDA) is the task of modifying a statistical model trained on labeled data from a source domain to achieve better performance on data from a target domain, with access to only unlabeled data in the target domain.", "Existing state-of-the-art UDA approaches use neural networks to le...
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[ "Natural language processing models learn word representations based on the distributional hypothesis, which asserts that word context (e.g., co-occurrence) correlates with meaning.", "We propose that n -grams composed of random character sequences, or garble , provide a novel context for studying word meaning bo...
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[ "Understanding procedural language requires reasoning about both hierarchical and temporal relations between events.", "For example, boiling pasta is a sub-event of making a pasta dish, typically happens before draining pasta, and requires the use of omitted tools (e.g. a strainer, sink...).", "While people are...
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[ "Extracting structured knowledge from product profiles is crucial for various applications in e-Commerce.", "State-of-the-art approaches for knowledge extraction were each designed for a single category of product, and thus do not apply to real-life e-Commerce scenarios, which often contain thousands of diverse c...
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[ "Existing pre-trained language models (PLMs) are often computationally expensive in inference, making them impractical in various resource-limited real-world applications.", "To address this issue, we propose a dynamic token reduction approach to accelerate PLMs' inference, named TR-BERT, which could flexibly ada...
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[ "Masked language model and autoregressive language model are two types of language models.", "While pretrained masked language models such as BERT (Devlin et al., 2019) overwhelm the line of natural language understanding (NLU) tasks, autoregressive language models such as GPT (Radford et al., 2018) are especiall...
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[ "Recent years have seen a flourishing of neural keyphrase generation (KPG) works, including the release of several large-scale datasets and a host of new models to tackle them.", "Model performance on KPG tasks has increased significantly with evolving deep learning research.", "However, there lacks a comprehen...
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[ "Recently, various response generation models for two-party conversations have achieved impressive improvements, but less effort has been paid to multi-party conversations (MPCs) which are more practical and complicated.", "Compared with a two-party conversation where a dialogue context is a sequence of utterance...
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[ "Capturing interactions among event arguments is an essential step towards robust event argument extraction (EAE).", "However, existing efforts in this direction suffer from two limitations: 1) The argument role type information of contextual entities is mainly utilized as training signals, ignoring the potential...
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[ "Cross-Lingual Word Embeddings (CLWEs) encode words from two or more languages in a shared high-dimensional space in which vectors representing words with similar meaning (regardless of language) are closely located.", "Existing methods for building high-quality CLWEs learn mappings that minimise the (cid:96) 2 n...
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[ "Recently, sentiment analysis has seen remarkable advance with the help of pre-training approaches.", "However, sentiment knowledge, such as sentiment words and aspect-sentiment pairs, is ignored in the process of pre-training, despite the fact that they are widely used in traditional sentiment analysis approache...
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[ "A major proportion of a text summary includes important entities found in the original text.", "These entities build up the topic of the summary.", "Moreover, they hold commonsense information once they are linked to a knowledge base.", "Based on these observations, this paper investigates the usage of linke...
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[ "Information extraction suffers from its varying targets, heterogeneous structures, and demand-specific schemas.", "In this paper, we propose a unified text-to-structure generation framework, namely UIE, which can universally model different IE tasks, adaptively generate targeted structures, and collaboratively l...
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[ "A good conversation requires balance between simplicity and detail; staying on topic and changing it; asking questions and answering them.", "Although dialogue agents are commonly evaluated via human judgments of overall quality, the relationship between quality and these individual factors is less well-studied...
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[ "Intent classification is a major task in spoken language understanding (SLU).", "Since most models are built with pre-collected in-domain (IND) training utterances, their ability to detect unsupported out-of-domain (OOD) utterances has a critical effect in practical use.", "Recent works have shown that using e...
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[ "Massively multilingual models for neural machine translation (NMT) are theoretically attractive, but often underperform bilingual models and deliver poor zero-shot translations.", "In this paper, we explore ways to improve them.", "We argue that multilingual NMT requires stronger modeling capacity to support l...
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[ "Legal Judgment Prediction (LJP) is the task of automatically predicting a law case's judgment results given a text describing its facts, which has excellent prospects in judicial assistance systems and convenient services for the public.", "In practice, confusing charges are frequent, because law cases applicabl...
[ "abstain", "abstain", "abstain", "objective", "objective", "objective", "abstain", "abstain", "abstain", "abstain", "abstain", "abstain", "abstain", "abstain", "abstain", "method", "abstain", "abstain", "abstain", "abstain", "objective", "abstain", "abstain", "result", ...
[ "Most language understanding models in task-oriented dialog systems are trained on a small amount of annotated training data, and evaluated in a small set from the same distribution.", "However, these models can lead to system failure or undesirable output when being exposed to natural language perturbation or va...
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[ "Linguistic Code-switching (CS) is still an understudied phenomenon in natural language processing.", "The NLP community has mostly focused on monolingual and multi-lingual scenarios, but little attention has been given to CS in particular.", "This is partly because of the lack of resources and annotated data, ...
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[ "Abstract Inferring missing links in knowledge graphs (KG) has attracted a lot of attention from the research community.", "In this paper, we tackle a practical query answering task involving predicting the relation of a given entity pair.", "We frame this prediction problem as an inference problem in a probabi...
[ "abstain", "method", "abstain", "method", "abstain", "abstain", "method", "abstain", "abstain", "abstain", "abstain", "abstain", "abstain", "objective", "abstain", "abstain", "abstain", "abstain", "abstain", "abstain", "abstain", "result", "abstain", "abstain", "absta...
[ "Structured document understanding has attracted considerable attention and made significant progress recently, owing to its crucial role in intelligent document processing.", "However, most existing related models can only deal with the document data of specific language(s) (typically English) included in the pr...
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[ "Current dialogue summarization systems usually encode the text with a number of general semantic features (e.g., keywords and topics) to gain more powerful dialogue modeling capabilities.", "However, these features are obtained via open-domain toolkits that are dialog-agnostic or heavily relied on human annotati...
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[ "When developing topic models, a critical question that should be asked is: How well will this model work in an applied setting?", "Because standard performance evaluation of topic interpretability uses automated measures modeled on human evaluation tests that are dissimilar to applied usage, these models' genera...
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[ "Automatically extracting key information from scientific documents has the potential to help scientists work more efficiently and accelerate the pace of scientific progress.", "Prior work has considered extracting document-level entity clusters and relations end-to-end from raw scientific text, which can improve...
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[ "We propose a novel constituency parsing model that casts the parsing problem into a series of pointing tasks.", "Specifically, our model estimates the likelihood of a span being a legitimate tree constituent via the pointing score corresponding to the boundary words of the span.", "Our parsing model supports e...
[ "objective", "abstain", "objective", "result", "result", "objective", "abstain", "abstain", "abstain", "abstain", "abstain", "abstain", "abstain", "abstain", "abstain", "abstain", "abstain", "abstain", "objective", "abstain", "abstain", "abstain", "abstain", "abstain", ...
[ "Automatic metrics are fundamental for the development and evaluation of machine translation systems.", "Judging whether, and to what extent, automatic metrics concur with the gold standard of human evaluation is not a straightforward problem.", "We show that current methods for judging metrics are highly sensi...
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[ "Learning high-quality embeddings for rare words is a hard problem because of sparse context information.", "Mimicking (Pinter et al., 2017) has been proposed as a solution: given embeddings learned by a standard algorithm, a model is first trained to reproduce embeddings of frequent words from their surface form...
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[ "Part-of-Speech (POS) tags routinely appear as features in morphological tasks.", "POS taggers are often one of the first NLP tools developed for low-resource languages.", "However, as NLP expands to new languages it cannot assume that POS tags will be available to train a POS tagger.", "This paper empiricall...
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[ "Crowdsourcing has emerged as a popular approach for collecting annotated data to train supervised machine learning models.", "However, annotator bias can lead to defective annotations.", "Though there are a few works investigating individual annotator bias, the group effects in annotators are largely overlooke...
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[ "Multi-modal techniques offer significant untapped potential to unlock improved NLP technology for local languages.", "However, many advances in language model pre-training are focused on text, a fact that only increases systematic inequalities in the performance of NLP tasks across the world's languages.", "In...
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[ "Personalized language models are designed and trained to capture language patterns specific to individual users.", "This makes them more accurate at predicting what a user will write.", "However, when a new user joins a platform and not enough text is available, it is harder to build effective personalized lan...
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[ "Thanks to the strong representation power of neural encoders, neural chart-based parsers have achieved highly competitive performance by using local features.", "Recently, it has been shown that non-local features in CRF structures lead to improvements.", "In this paper, we investigate injecting non-local feat...
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[ "Although deep neural networks have achieved prominent performance on many NLP tasks, they are vulnerable to adversarial examples.", "We propose Dirichlet Neighborhood Ensemble (DNE), a randomized method for training a robust model to defense synonym substitution-based attacks.", "During training, DNE forms vir...
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[ "In human-level NLP tasks, such as predicting mental health, personality, or demographics, the number of observations is often smaller than the standard 768+ hidden state sizes of each layer within modern transformer-based language models, limiting the ability to effectively leverage transformers.", "Here, we pro...
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[ "Machine Learning has been the quintessential solution for many AI problems, but learning models are heavily dependent on specific training data.", "Some learning models can be incorporated with prior knowledge using a Bayesian setup, but these learning models do not have the ability to access any organized world...
[ "abstain", "abstain", "objective", "objective", "method", "objective", "result", "objective", "abstain", "abstain", "abstain", "objective", "abstain", "abstain", "abstain", "abstain", "abstain", "abstain", "abstain", "objective", "method", "abstain", "abstain", "abstain...
[ "Recently, finetuning a pretrained language model to capture the similarity between sentence embeddings has shown the state-of-the-art performance on the semantic textual similarity (STS) task.", "However, the absence of an interpretation method for the sentence similarity makes it difficult to explain the model ...
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