State of the Art Models

Previous work demonstrated that web counts can be used to approximate bigram frequen- cies, and thus should be useful for a wide va- riety of NLP tasks. So far, only …...

. We present a new implication of Wu’s (1997) Inversion Transduction Grammar (ITG) Hypothesis, on the problem of retriev- ing truly parallel sentence translations from large collections of highly non-parallel …...

This paper presents a new, exemplar-based model of thematic fit. In contrast to pre- vious models, it does not approximate thematic fit as argument plausibility or ‘fit with verb selectional …...

The sense of a preposition is related to the semantics of its dominating prepositional phrase. Knowing the sense of a prepo- sition could help to correctly classify the semantic role …...

Morphology and syntax interact considerably in many languages and language processing should pay attention to these interdependen- cies. We analyze the effect of syntactic fea- tures when used in automatic …...

This paper presents a novel approach using recurrent neural networks for estimating the quality of machine translation output. A se- quence of vectors made by the prediction method is used …...

In this paper, we propose a neural network model for graph-based dependency pars- ing which utilizes Bidirectional LSTM (BLSTM) to capture richer contextual in- formation instead of using high-order fac- …...

Morphological inflection generation is the task of generating the inflected form of a given lemma corresponding to a particular linguis- tic transformation. We model the problem of inflection generation as …...

AbstractWord embeddings are widely used in Natural Language Processing, mainly due to their success in capturing semantic information from massive corpora. However, their creation process does not allow the different …...

AbstractWe present an unsupervised model of dialogue act sequences in conversation. By modeling topical themes as transitioning more slowly than dialogue acts in conversation, our model de-emphasizes content-related words in …...

AbstractWe present RACE, a new dataset for benchmark evaluation of methods in the reading comprehension task. Collected from the English exams for middle and high school Chinese students in the …...

AbstractMulti-lingual relation extraction aims to find unknown relational facts from text in various languages. Existing models cannot well capture the consistency and diversity of relation patterns in different languages. To …...

While extractive summarization is a well stud- ied problem, it is far from solved. In recent years a large number of interesting and com- plex models have been used to …...

AbstractThe availability of large-scale online social data, coupled with computational methods can help us answer fundamental questions relat- ing to our social lives, particularly our health and well-being. The #MeToo …...

AbstractCloze-style reading comprehension in Chinese is still limited due to the lack of various corpora. In this paper we propose a large-scale Chinese cloze test dataset ChID, which studies the …...

AbstractRelation extraction is the task of determining the relation between two entities in a sentence. Distantly-supervised models are popular for this task. However, sentences can be long and two entities …...

AbstractDeep-learning-based models have been successfully applied to the problem of detecting fake news on social media. While the correlations among news articles have been shown to be effective cues for …...

AbstractRecent work by Zellers et al. (2018) introduced a new task of commonsense natural language inference: given an event description such as “A woman sits at a piano,” a machine …...

AbstractNeural network models have been actively applied to word segmentation, especially Chinese, because of the ability to minimize the effort in feature engineering. Typical segmentation models are categorized as character-based, …...

The Tibetan language, despite being spoken by 8 million people, is a low- resource language in NLP terms, and research to develop NLP tools and re- sources for the language …...

AbstractParaphrase generation is an interesting and challenging NLP task which has numerous practical applications. In this paper, we analyze datasets commonly used for paraphrase generation research, and show that simply …...

AbstractUsers participate in online discussion forums to learn from others and share their knowledge with the community. They often start a thread with a question or by sharing their new …...

AbstractIn aspect-level sentiment classification (ASC), it is prevalent to equip dominant neural models with attention mechanisms, for the sake of acquiring the importance of each context word on the given …...

AbstractRecent years have seen important advances in the quality of state-of-the-art models, but this has come at the expense of models becoming less interpretable. This survey presents an overview of …...

AbstractThis paper tackles the task of named entity recognition (NER) applied to digitized historical texts obtained from processing digital images of newspapers using optical character recognition (OCR) techniques. We argue …...

AbstractThis paper introduces BD2BB, a novel language and vision benchmark that requires multimodal models combine complementary information from the two modalities. Recently, impressive progress has been made to develop universal …...

AbstractIn visual media, text emphasis is the strengthening of words in a text to convey the intent of the author. Text emphasis in visual media is generally done by using …...

AbstractLinking of biomedical entity mentions to various terminologies of chemicals, diseases, genes, adverse drug reactions is a challenging task, often requiring non-syntactic interpretation. A large number of biomedical corpora and …...

AbstractEvent extraction plays an important role in legal applications, including case push and auxiliary judgment. However, traditional event structure cannot express the connections between arguments, which are extremely important in …...

AbstractThe CoNLL-2003 corpus for English-language named entity recognition (NER) is one of the most influential corpora for NER model research. A large number of publications, including many landmark works, have …...

AbstractOpen-domain Keyphrase extraction (KPE) on the Web is a fundamental yet complex NLP task with a wide range of practical applications within the field of Information Retrieval. In contrast to …...

AbstractSentence fusion is the task of joining related sentences into coherent text. Current training and evaluation schemes for this task are based on single reference ground-truths and do not account …...

AbstractThe task of graph-to-text generation aims at producing sentences that preserve the meaning of input graphs. As a crucial defect, the current state-of-the-art models may mess up or even drop …...

AbstractThe ambiguous annotation criteria lead to divergence of Chinese Word Segmentation (CWS) datasets in various granularities. Multi-criteria Chinese word segmentation aims to capture various annotation criteria among datasets and leverage …...

AbstractPronouns are often dropped in Chinese conversations and recovering the dropped pronouns is important for NLP applications such as Machine Translation. Existing approaches usually formulate this as a sequence labeling …...

In end-to-end speech translation, acoustic rep- resentations learned by the encoder are usually fixed and static, from the perspective of the de- coder, which is not desirable for dealing with …...

AbstractCharacter-based word-segmentation models have been extensively applied to agglutinative languages, including Thai, due to their high performance. These models estimate word boundaries from a character sequence. However, a character unit …...

AbstractCoreference resolution is essential for natural language understanding and has been long studied in NLP. In recent years, as the format of Question Answering (QA) became a standard for machine …...

Emphasizing words in presentation slides al- lows viewers to direct their gaze to focal points without reading the entire slide, retaining their attention on the speaker. Despite many stud- ies …...

AbstractNeural-based summarization models suffer from the length limitation of text encoder. Long documents have to been truncated before they are sent to the model, which results in huge loss of …...

AbstractEvaluation of open-domain dialogue systems is highly challenging and development of better techniques is highlighted time and again as desperately needed. Despite substantial efforts to carry out reliable live evaluation …...

AbstractIn this paper, we propose a simple yet effective way to generate pun sentences that does not require any training on existing puns. Our approach is inspired by humor theories …...

AbstractThe use of misogynistic and sexist language has increased in recent years in social media, and is increasing in the Arabic world in reaction to reforms attempting to remove restrictions …...

AbstractThe Chinese text correction (CTC) focuses on detecting and correcting Chinese spelling errors and grammatical errors. Most existing datasets of Chinese spelling check (CSC) and Chinese grammatical error correction (GEC) …...

AbstractOpinion summarization focuses on generating summaries that reflect popular subjective information expressed in multiple online reviews. While generated summaries offer general and concise information about a particular hotel or product, …...

AbstractUnderstanding causality has vital importance for various Natural Language Processing (NLP) applications. Beyond the labeled instances, conceptual explanations of the causality can provide deep understanding of the causal fact to …...

AbstractDespite significant interest in developing general purpose fact checking models, it is challenging to construct a large-scale fact verification dataset with realistic real-world claims. Existing claims are either authored by …...

AbstractAutomatic morphological processing can aid downstream natural language processing applications, especially for low-resource languages, and assist language documentation efforts for endangered languages. Having long been multilingual, the field of computational …...

AbstractThis paper introduces a novel Self-supervised Fine-grained Dialogue Evaluation framework (SelF-Eval). The core idea is to model the correlation between turn quality and the entire dialogue quality. We first propose …...

AbstractLegal judgment prediction (LJP) is a fundamental task in legal AI, which aims to assist the judge to hear the case and determine the judgment. The legal judgment usually consists …...

AbstractDocument-level relation extraction (DocRE) attracts more research interest recently. While models achieve consistent performance gains in DocRE, their underlying decision rules are still understudied: Do they make the right predictions …...

AbstractIn this paper, we propose DiffusionNER, which formulates the named entity recognition task as a boundary-denoising diffusion process and thus generates named entities from noisy spans. During training, DiffusionNER gradually …...

AbstractMost event detection methods act at the sentence-level and focus on identifying sentences related to a particular event. However, identifying certain parts of a sentence that act as event triggers …...