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Most Influential NAACL Papers (2023-04)

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The North American Chapter of the Association for Computational Linguistics (NAACL) is one of the top natural language processing conferences in the world. Paper Digest Team analyzes all papers published on NAACL in the past years, and presents the 15 most influential papers for each year. This ranking list is automatically constructed based upon citations from both research papers and granted patents, and will be frequently updated to reflect the most recent changes. To find the latest version of this list or the most influential papers from other conferences/journals, please visit Best Paper Digest page. Note: the most influential papers may or may not include the papers that won the best paper awards. (Version: 2023-04)

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TABLE 1: Most Influential NAACL Papers (2023-04)

Year Rank Paper Author(s)
2022 1 FNet: Mixing Tokens with Fourier Transforms
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Highlight: We show that Transformer encoder architectures can be sped up, with limited accuracy costs, by replacing the self-attention sublayers with simple linear transformations that mix input tokens.		 James Lee-Thorp; Joshua Ainslie; Ilya Eckstein; Santiago Ontanon;
2022 2 Learning To Retrieve Prompts for In-Context Learning
IF:3   Related Papers   Related Patents   Related Grants   Related Orgs   Related Experts   View
Highlight: In this work, we propose an efficient method for retrieving prompts for in-context learning using annotated data and an LM.		 Ohad Rubin; Jonathan Herzig; Jonathan Berant;
2022 3 MetaICL: Learning to Learn In Context
IF:3   Related Papers   Related Patents   Related Grants   Related Orgs   Related Experts   View
Highlight: We introduce MetaICL (Meta-training for In-Context Learning), a new meta-training framework for few-shot learning where a pretrained language model is tuned to do in-context learning on a large set of training tasks.		 Sewon Min; Mike Lewis; Luke Zettlemoyer; Hannaneh Hajishirzi;
2022 4 ColBERTv2: Effective and Efficient Retrieval Via Lightweight Late Interaction
IF:3   Related Papers   Related Patents   Related Grants   Related Orgs   Related Experts   View
Highlight: In this work, we introduce Maize, a retriever that couples an aggressive residual compression mechanism with a denoised supervision strategy to simultaneously improve the quality and space footprint of late interaction.		 Keshav Santhanam; Omar Khattab; Jon Saad-Falcon; Christopher Potts; Matei Zaharia;
2022 5 Do Prompt-Based Models Really Understand The Meaning of Their Prompts?
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Highlight: In this study, we experiment with over 30 prompts manually written for natural language inference (NLI).		 Albert Webson; Ellie Pavlick;
2022 6 Symbolic Knowledge Distillation: from General Language Models to Commonsense Models
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Highlight: In this work, we investigate an alternative, from-machine-to-corpus-to-machine: general language models author these commonsense knowledge graphs to train commonsense models.		 PETER WEST et. al.
2022 7 Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detection
IF:3   Related Papers   Related Patents   Related Grants   Related Orgs   Related Experts   View
Highlight: We seek to understand the *who*, *why*, and *what* behind biases in toxicity annotations.		 MAARTEN SAP et. al.
2022 8 GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval
IF:3   Related Papers   Related Patents   Related Grants   Related Orgs   Related Experts   View
Highlight: In this paper, we propose the novel unsupervised domain adaptation method Generative Pseudo Labeling (GPL), which combines a query generator with pseudo labeling from a cross-encoder.		 Kexin Wang; Nandan Thakur; Nils Reimers; Iryna Gurevych;
2022 9 Template-free Prompt Tuning for Few-shot NER
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Highlight: In this work, we propose a more elegant method to reformulate NER tasks as LM problems without any templates.		 RUOTIAN MA et. al.
2022 10 DEMix Layers: Disentangling Domains for Modular Language Modeling
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Highlight: We introduce a new domain expert mixture (DEMix) layer that enables conditioning a language model (LM) on the domain of the input text.		 Suchin Gururangan; Mike Lewis; Ari Holtzman; Noah Smith; Luke Zettlemoyer;
2022 11 DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings
IF:3   Related Papers   Related Patents   Related Grants   Related Orgs   Related Experts   View
Highlight: We propose DiffCSE, an unsupervised contrastive learning framework for learning sentence embeddings.		 YUNG-SUNG CHUANG et. al.
2022 12 Reframing Human-AI Collaboration for Generating Free-Text Explanations
IF:3   Related Papers   Related Patents   Related Grants   Related Orgs   Related Experts   View
Highlight: We consider the task of generating free-text explanations using human-written examples in a few-shot manner.		 Sarah Wiegreffe; Jack Hessel; Swabha Swayamdipta; Mark Riedl; Yejin Choi;
2022 13 Textless Speech-to-Speech Translation on Real Data
IF:3   Related Papers   Related Patents   Related Grants   Related Orgs   Related Experts   View
Highlight: We present a textless speech-to-speech translation (S2ST) system that can translate speech from one language into another language and can be built without the need of any text data.		 ANN LEE et. al.
2022 14 KAT: A Knowledge Augmented Transformer for Vision-and-Language
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Highlight: In this work, we ask a complementary question: Can multimodal transformers leverage explicit knowledge in their reasoning?		 LIANGKE GUI et. al.
2022 15 NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristics
IF:3   Related Papers   Related Patents   Related Grants   Related Orgs   Related Experts   View
Highlight: Drawing inspiration from the A* search algorithm, we propose NeuroLogic A*esque, a decoding algorithm that incorporates heuristic estimates of future cost.		 XIMING LU et. al.
2021 1 MT5: A Massively Multilingual Pre-trained Text-to-Text Transformer
IF:7   Related Papers   Related Patents   Related Grants   Related Orgs   Related Experts   View
Highlight: In this paper, we introduce mT5, a multilingual variant of T5 that was pre-trained on a new Common Crawl-based dataset covering 101 languages.		 LINTING XUE et. al.
2021 2 RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering
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Highlight: To address these challenges, we propose an optimized training approach, called RocketQA, to improving dense passage retrieval.		 YINGQI QU et. al.
2021 3 Unified Pre-training for Program Understanding and Generation
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Highlight: This paper introduces PLBART, a sequence-to-sequence model capable of performing a broad spectrum of program and language understanding and generation tasks.		 Wasi Ahmad; Saikat Chakraborty; Baishakhi Ray; Kai-Wei Chang;
2021 4 KILT: A Benchmark for Knowledge Intensive Language Tasks
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Highlight: To catalyze research on models that condition on specific information in large textual resources, we present a benchmark for knowledge-intensive language tasks (KILT).		 FABIO PETRONI et. al.
2021 5 InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training
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Highlight: In this work, we present an information-theoretic framework that formulates cross-lingual language model pre-training as maximizing mutual information between multilingual-multi-granularity texts.		 ZEWEN CHI et. al.
2021 6 Learning How to Ask: Querying LMs with Mixtures of Soft Prompts
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Highlight: We explore the idea of learning prompts by gradient descent-either fine-tuning prompts taken from previous work, or starting from random initialization.		 Guanghui Qin; Jason Eisner;
2021 7 QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering
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Highlight: Here we propose a new model, QA-GNN, which addresses the above challenges through two key innovations: (i) relevance scoring, where we use LMs to estimate the importance of KG nodes relative to the given QA context, and (ii) joint reasoning, where we connect the QA context and KG to form a joint graph, and mutually update their representations through graph-based message passing.		 Michihiro Yasunaga; Hongyu Ren; Antoine Bosselut; Percy Liang; Jure Leskovec;
2021 8 How Many Data Points Is A Prompt Worth?
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Highlight: We aim to quantify this benefit through rigorous testing of prompts in a fair setting: comparing prompted and head-based fine-tuning in equal conditions across many tasks and data sizes.		 Teven Le Scao; Alexander Rush;
2021 9 A Frustratingly Easy Approach for Entity and Relation Extraction
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Highlight: In this work, we present a simple pipelined approach for entity and relation extraction, and establish the new state-of-the-art on standard benchmarks (ACE04, ACE05 and SciERC), obtaining a 1.7%-2.8% absolute improvement in relation F1 over previous joint models with the same pre-trained encoders.		 Zexuan Zhong; Danqi Chen;
2021 10 Dynabench: Rethinking Benchmarking in NLP
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Highlight: In this paper, we argue that Dynabench addresses a critical need in our community: contemporary models quickly achieve outstanding performance on benchmark tasks but nonetheless fail on simple challenge examples and falter in real-world scenarios.		 DOUWE KIELA et. al.
2021 11 Factual Probing Is [MASK]: Learning Vs. Learning to Recall
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Highlight: In this work, we make two complementary contributions to better understand these factual probing techniques.		 Zexuan Zhong; Dan Friedman; Danqi Chen;
2021 12 GSum: A General Framework for Guided Neural Abstractive Summarization
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Highlight: In this paper, we propose a general and extensible guided summarization framework (GSum) that can effectively take different kinds of external guidance as input, and we perform experiments across several different varieties.		 Zi-Yi Dou; Pengfei Liu; Hiroaki Hayashi; Zhengbao Jiang; Graham Neubig;
2021 13 Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics
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Highlight: To address these limitations, we devise a typology of factual errors and use it to collect human annotations of generated summaries from state-of-the-art summarization systems for the CNN/DM and XSum datasets.		 Artidoro Pagnoni; Vidhisha Balachandran; Yulia Tsvetkov;
2021 14 Self-Alignment Pretraining for Biomedical Entity Representations
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Highlight: To address this challenge, we propose SapBERT, a pretraining scheme that self-aligns the representation space of biomedical entities.		 Fangyu Liu; Ehsan Shareghi; Zaiqiao Meng; Marco Basaldella; Nigel Collier;
2021 15 Self-training Improves Pre-training for Natural Language Understanding
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Highlight: In this paper, we study self-training as another way to leverage unlabeled data through semi-supervised learning.		 JINGFEI DU et. al.
2019 1 BERT: Pre-training Of Deep Bidirectional Transformers For Language Understanding
IF:10   Related Papers   Related Patents   Related Grants   Related Orgs   Related Experts   View
Highlight: We introduce a new language representation model called BERT, which stands for Bidirectional Encoder Representations from Transformers.		 Jacob Devlin; Ming-Wei Chang; Kenton Lee; Kristina Toutanova,;
2019 2 Attention Is Not Explanation
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Highlight: In this work we perform extensive experiments across a variety of NLP tasks that aim to assess the degree to which attention weights provide meaningful explanations for predictions.		 Sarthak Jain; Byron C. Wallace,;
2019 3 A Structural Probe For Finding Syntax In Word Representations
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Highlight: In this work, we propose a structural probe, which evaluates whether syntax trees are embedded in a linear transformation of a neural network’s word representation space.		 John Hewitt; Christopher D. Manning,;
2019 4 CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge
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Highlight: To investigate question answering with prior knowledge, we present CommonsenseQA: a challenging new dataset for commonsense question answering.		 Alon Talmor; Jonathan Herzig; Nicholas Lourie; Jonathan Berant,;
2019 5 Linguistic Knowledge And Transferability Of Contextual Representations
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Highlight: To shed light on the linguistic knowledge they capture, we study the representations produced by several recent pretrained contextualizers (variants of ELMo, the OpenAI transformer language model, and BERT) with a suite of sixteen diverse probing tasks.		 Nelson F. Liu; Matt Gardner; Yonatan Belinkov; Matthew E. Peters; Noah A. Smith,;
2019 6 Predicting The Type And Target Of Offensive Posts In Social Media
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Highlight: In contrast, here we target several different kinds of offensive content.		 MARCOS ZAMPIERI et. al.
2019 7 DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs
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Highlight: We introduce a new reading comprehension benchmark, DROP, which requires Discrete Reasoning Over the content of Paragraphs.		 DHEERU DUA et. al.
2019 8 BERT Post-Training For Review Reading Comprehension And Aspect-based Sentiment Analysis
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Highlight: We call this problem Review Reading Comprehension (RRC). In this work, we first build an RRC dataset called ReviewRC based on a popular benchmark for aspect-based sentiment analysis.		 Hu Xu; Bing Liu; Lei Shu; Philip Yu,;
2019 9 Lipstick On A Pig: Debiasing Methods Cover Up Systematic Gender Biases In Word Embeddings But Do Not Remove Them
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Highlight: Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them.		 Hila Gonen; Yoav Goldberg,;
2019 10 Utilizing BERT For Aspect-Based Sentiment Analysis Via Constructing Auxiliary Sentence
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Highlight: In this paper, we construct an auxiliary sentence from the aspect and convert ABSA to a sentence-pair classification task, such as question answering (QA) and natural language inference (NLI).		 Chi Sun; Luyao Huang; Xipeng Qiu,;
2019 11 Analysis Methods In Neural Language Processing: A Survey
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Highlight: In this survey paper, we review analysis methods in neural language processing, categorize them according to prominent research trends, highlight existing limitations, and point to potential directions for future work.		 Yonatan Belinkov; James Glass,;
2019 12 Massively Multilingual Neural Machine Translation
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Highlight: We perform extensive experiments in training massively multilingual NMT models, involving up to 103 distinct languages and 204 translation directions simultaneously.		 Roee Aharoni; Melvin Johnson; Orhan Firat,;
2019 13 BoolQ: Exploring The Surprising Difficulty Of Natural Yes/No Questions
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Highlight: In this paper we study yes/no questions that are naturally occurring – meaning that they are generated in unprompted and unconstrained settings. We build a reading comprehension dataset, BoolQ, of such questions, and show that they are unexpectedly challenging.		 CHRISTOPHER CLARK et. al.
2019 14 On Measuring Social Biases In Sentence Encoders
IF:5   Related Papers   Related Patents   Related Grants   Related Orgs   Related Experts   View
Highlight: Accordingly, we extend the Word Embedding Association Test to measure bias in sentence encoders.		 Chandler May; Alex Wang; Shikha Bordia; Samuel R. Bowman; Rachel Rudinger,;
2019 15 PAWS: Paraphrase Adversaries From Word Scrambling
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Highlight: This paper introduces PAWS (Paraphrase Adversaries from Word Scrambling), a new dataset with 108,463 well-formed paraphrase and non-paraphrase pairs with high lexical overlap.		 Yuan Zhang; Jason Baldridge; Luheng He,;
2018 1 Deep Contextualized Word Representations
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Highlight: We introduce a new type of deep contextualized word representation that models both (1) complex characteristics of word use (e.g., syntax and semantics), and (2) how these uses vary across linguistic contexts (i.e., to model polysemy).		 MATTHEW PETERS et. al.
2018 2 A Broad-Coverage Challenge Corpus For Sentence Understanding Through Inference
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Highlight: This paper introduces the Multi-Genre Natural Language Inference (MultiNLI) corpus, a dataset designed for use in the development and evaluation of machine learning models for sentence understanding.		 Adina Williams; Nikita Nangia; Samuel Bowman;
2018 3 Self-Attention With Relative Position Representations
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Highlight: In this work we present an alternative approach, extending the self-attention mechanism to efficiently consider representations of the relative positions, or distances between sequence elements.		 Peter Shaw; Jakob Uszkoreit; Ashish Vaswani;
2018 4 Annotation Artifacts In Natural Language Inference Data
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Highlight: We show that, in a significant portion of such data, this protocol leaves clues that make it possible to identify the label by looking only at the hypothesis, without observing the premise.		 SUCHIN GURURANGAN et. al.
2018 5 FEVER: A Large-scale Dataset For Fact Extraction And VERification
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Highlight: In this paper we introduce a new publicly available dataset for verification against textual sources, FEVER: Fact Extraction and VERification.		 James Thorne; Andreas Vlachos; Christos Christodoulopoulos; Arpit Mittal;
2018 6 Unsupervised Learning Of Sentence Embeddings Using Compositional N-Gram Features
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Highlight: We present a simple but efficient unsupervised objective to train distributed representations of sentences.		 Matteo Pagliardini; Prakhar Gupta; Martin Jaggi;
2018 7 Adversarial Example Generation With Syntactically Controlled Paraphrase Networks
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Highlight: We propose syntactically controlled paraphrase networks (SCPNs) and use them to generate adversarial examples.		 Mohit Iyyer; John Wieting; Kevin Gimpel; Luke Zettlemoyer;
2018 8 Gender Bias In Coreference Resolution: Evaluation And Debiasing Methods
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Highlight: In this paper, we introduce a new benchmark for co-reference resolution focused on gender bias, WinoBias.		 Jieyu Zhao; Tianlu Wang; Mark Yatskar; Vicente Ordonez; Kai-Wei Chang;
2018 9 Ranking Sentences For Extractive Summarization With Reinforcement Learning
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Highlight: In this paper we conceptualize extractive summarization as a sentence ranking task and propose a novel training algorithm which globally optimizes the ROUGE evaluation metric through a reinforcement learning objective.		 Shashi Narayan; Shay B. Cohen; Mirella Lapata;
2018 10 A Novel Embedding Model For Knowledge Base Completion Based On Convolutional Neural Network
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Highlight: In this paper, we propose a novel embedding model, named ConvKB, for knowledge base completion.		 Dai Quoc Nguyen; Tu Dinh Nguyen; Dat Quoc Nguyen; Dinh Phung;
2018 11 Delete, Retrieve, Generate: A Simple Approach To Sentiment And Style Transfer
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Highlight: In this paper, we propose simpler methods motivated by the observation that text attributes are often marked by distinctive phrases (e.g., too small).		 Juncen Li; Robin Jia; He He; Percy Liang;
2018 12 A Discourse-Aware Attention Model For Abstractive Summarization Of Long Documents
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Highlight: We propose the first model for abstractive summarization of single, longer-form documents (e.g., research papers).		 ARMAN COHAN et. al.
2018 13 Contextual Augmentation: Data Augmentation By Words With Paradigmatic Relations
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Highlight: We propose a novel data augmentation for labeled sentences called contextual augmentation.		 Sosuke Kobayashi;
2018 14 Colorless Green Recurrent Networks Dream Hierarchically
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Highlight: We investigate to what extent RNNs learn to track abstract hierarchical syntactic structure.		 Kristina Gulordava; Piotr Bojanowski; Edouard Grave; Tal Linzen; Marco Baroni;
2018 15 Explainable Prediction Of Medical Codes From Clinical Text
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Highlight: We present an attentional convolutional network that predicts medical codes from clinical text.		 James Mullenbach; Sarah Wiegreffe; Jon Duke; Jimeng Sun; Jacob Eisenstein;
2016 1 Hierarchical Attention Networks For Document Classification
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 ZICHAO YANG et. al.
2016 2 Neural Architectures For Named Entity Recognition
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 Guillaume Lample; Miguel Ballesteros; Sandeep Subramanian; Kazuya Kawakami; Chris Dyer;
2016 3 A Diversity-Promoting Objective Function For Neural Conversation Models
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 Jiwei Li; Michel Galley; Chris Brockett; Jianfeng Gao; Bill Dolan;
2016 4 Abstractive Sentence Summarization With Attentive Recurrent Neural Networks
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 Sumit Chopra; Michael Auli; Alexander M. Rush;
2016 5 Visualizing And Understanding Neural Models In NLP
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 Jiwei Li; Xinlei Chen; Eduard Hovy; Dan Jurafsky;
2016 6 Multi-Way, Multilingual Neural Machine Translation With A Shared Attention Mechanism
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 Orhan Firat; Kyunghyun Cho; Yoshua Bengio;
2016 7 Learning To Compose Neural Networks For Question Answering
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 Jacob Andreas; Marcus Rohrbach; Trevor Darrell; Dan Klein;
2016 8 Learning Distributed Representations Of Sentences From Unlabelled Data
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 Felix Hill; Kyunghyun Cho; Anna Korhonen;
2016 9 Recurrent Neural Network Grammars
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 Chris Dyer; Adhiguna Kuncoro; Miguel Ballesteros; Noah A. Smith;
2016 10 A Corpus And Cloze Evaluation For Deeper Understanding Of Commonsense Stories
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 NASRIN MOSTAFAZADEH et. al.
2016 11 Joint Event Extraction Via Recurrent Neural Networks
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 Thien Huu Nguyen; Kyunghyun Cho; Ralph Grishman;
2016 12 Sequential Short-Text Classification With Recurrent And Convolutional Neural Networks
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 Ji Young Lee; Franck Dernoncourt;
2016 13 Learning Natural Language Inference With LSTM
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 Shuohang Wang; Jing Jiang;
2016 14 Counter-fitting Word Vectors To Linguistic Constraints
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 NIKOLA MRKŠIĆ et. al.
2016 15 Emergent: A Novel Data-set For Stance Classification
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 William Ferreira; Andreas Vlachos;
2015 1 A Neural Network Approach To Context-Sensitive Generation Of Conversational Responses
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 ALESSANDRO SORDONI et. al.
2015 2 Effective Use Of Word Order For Text Categorization With Convolutional Neural Networks
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 Rie Johnson; Tong Zhang;
2015 3 Representation Learning Using Multi-Task Deep Neural Networks For Semantic Classification And Information Retrieval
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 XIAODONG LIU et. al.
2015 4 Two/Too Simple Adaptations Of Word2Vec For Syntax Problems
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 Wang Ling; Chris Dyer; Alan W. Black; Isabel Trancoso;
2015 5 Normalized Word Embedding And Orthogonal Transform For Bilingual Word Translation
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 Chao Xing; Dong Wang; Chao Liu; Yiye Lin;
2015 6 Combining Language And Vision With A Multimodal Skip-gram Model
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 Angeliki Lazaridou; Nghia The Pham; Marco Baroni;
2015 7 Toward Abstractive Summarization Using Semantic Representations
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 Fei Liu; Jeffrey Flanigan; Sam Thomson; Norman Sadeh; Noah A. Smith;
2015 8 Injecting Logical Background Knowledge Into Embeddings For Relation Extraction
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 Tim Rocktäschel; Sameer Singh; Sebastian Riedel;
2015 9 Do Supervised Distributional Methods Really Learn Lexical Inference Relations?
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2015 10 Convolutional Neural Network For Paraphrase Identification
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2015 11 Translating Videos To Natural Language Using Deep Recurrent Neural Networks
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2015 12 A Transition-based Algorithm For AMR Parsing
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2015 13 Not All Character N-grams Are Created Equal: A Study In Authorship Attribution
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2015 14 Lexicon-Free Conversational Speech Recognition With Neural Networks
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2015 15 Sentiment After Translation: A Case-Study On Arabic Social Media Posts
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2013 1 Linguistic Regularities In Continuous Space Word Representations
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2013 2 A Simple, Fast, And Effective Reparameterization Of IBM Model 2
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2013 3 Improved Part-of-Speech Tagging For Online Conversational Text With Word Clusters
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2013 4 PPDB: The Paraphrase Database
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2013 5 Relation Extraction With Matrix Factorization And Universal Schemas
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2013 6 Negative Deceptive Opinion Spam
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2013 7 What To Do About Bad Language On The Internet
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2013 8 Separating Fact From Fear: Tracking Flu Infections On Twitter
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2013 9 Learning Whom To Trust With MACE
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2013 10 Distant Supervision For Relation Extraction With An Incomplete Knowledge Base
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2013 11 Answer Extraction As Sequence Tagging With Tree Edit Distance
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2013 12 To Link Or Not To Link? A Study On End-to-End Tweet Entity Linking
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2013 13 Labeling The Languages Of Words In Mixed-Language Documents Using Weakly Supervised Methods
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2013 14 The Life And Death Of Discourse Entities: Identifying Singleton Mentions
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2013 15 Supervised Learning Of Complete Morphological Paradigms
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2012 1 Batch Tuning Strategies For Statistical Machine Translation
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2012 2 Learning From Bullying Traces In Social Media
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2012 3 Better Evaluation For Grammatical Error Correction
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2012 4 Cross-lingual Word Clusters For Direct Transfer Of Linguistic Structure
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2012 5 Re-examining Machine Translation Metrics For Paraphrase Identification
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2012 6 Stance Classification Using Dialogic Properties Of Persuasion
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2012 7 Structured Perceptron With Inexact Search
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2012 8 Machine Translation Of Arabic Dialects
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2012 9 Continuous Space Translation Models With Neural Networks
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2012 10 Using Paraphrases For Improving First Story Detection In News And Twitter
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2012 11 Context-Enhanced Citation Sentiment Detection
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2012 12 Stylometric Analysis Of Scientific Articles
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2012 13 Acoustic-Prosodic Entrainment And Social Behavior
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2012 14 Predicting Responses To Microblog Posts
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2012 15 Structured Event Retrieval Over Microblog Archives
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2010 1 Automatic Evaluation Of Topic Coherence
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2010 2 Streaming First Story Detection With Application To Twitter
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2010 3 An Unsupervised Aspect-Sentiment Model For Online Reviews
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2010 4 Unsupervised Modeling Of Twitter Conversations
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2010 5 Multi-document Summarization Via Budgeted Maximization Of Submodular Functions
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2010 6 Multi-Prototype Vector-Space Models Of Word Meaning
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2010 7 Good Question! Statistical Ranking For Question Generation
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2010 8 Dependency Tree-based Sentiment Classification Using CRFs With Hidden Variables
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2010 9 Distributed Training Strategies For The Structured Perceptron
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2010 10 Tree Edit Models For Recognizing Textual Entailments, Paraphrases, And Answers To Questions
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2010 11 Painless Unsupervised Learning With Features
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2010 12 Extracting Parallel Sentences From Comparable Corpora Using Document Level Alignment
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2010 13 The Viability Of Web-derived Polarity Lexicons
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2010 14 Movie Reviews And Revenues: An Experiment In Text Regression
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2010 15 Summarizing Microblogs Automatically
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2009 1 A Study On Similarity And Relatedness Using Distributional And WordNet-based Approaches
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2009 2 Exploring Content Models For Multi-Document Summarization
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2009 3 Joint Parsing And Named Entity Recognition
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2009 4 Predicting Risk From Financial Reports With Regression
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2009 5 Geo-Centric Language Models For Local Business Voice Search
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2009 6 Online EM For Unsupervised Models
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2009 7 11,001 New Features For Statistical Machine Translation
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2009 8 Unsupervised Approaches For Automatic Keyword Extraction Using Meeting Transcripts
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2009 9 Hierarchical Bayesian Domain Adaptation
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2009 10 Unsupervised Morphological Segmentation With Log-Linear Models
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2009 11 More Than Words: Syntactic Packaging And Implicit Sentiment
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2009 12 Improving Nonparameteric Bayesian Inference: Experiments On Unsupervised Word Segmentation With Adaptor Grammars
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2009 13 Improving Unsupervised Dependency Parsing With Richer Contexts And Smoothing
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2009 14 Using Citations To Generate Surveys Of Scientific Paradigms
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2009 15 Using A Dependency Parser To Improve SMT For Subject-Object-Verb Languages
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2007 1 Improved Inference For Unlexicalized Parsing
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2007 2 Multiple Aspect Ranking Using The Good Grief Algorithm
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2007 3 Agenda-Based User Simulation For Bootstrapping A POMDP Dialogue System
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2007 4 Using Wikipedia For Automatic Word Sense Disambiguation
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2007 5 Improving Diversity In Ranking Using Absorbing Random Walks
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2007 6 Combining Lexical And Grammatical Features To Improve Readability Measures For First And Second Language Texts
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2007 7 Bayesian Inference For PCFGs Via Markov Chain Monte Carlo
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2007 8 Applying Many-to-Many Alignments And Hidden Markov Models To Letter-to-Phoneme Conversion
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2007 9 Statistical Phrase-Based Post-Editing
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2007 10 Combining Outputs From Multiple Machine Translation Systems
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2007 11 A Systematic Exploration Of The Feature Space For Relation Extraction
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2007 12 A Comparison Of Pivot Methods For Phrase-Based Statistical Machine Translation
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2007 13 First-Order Probabilistic Models For Coreference Resolution
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2007 14 Joint Determination Of Anaphoricity And Coreference Resolution Using Integer Programming
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2007 15 Automating Creation Of Hierarchical Faceted Metadata Structures
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2006 1 OntoNotes: The 90% Solution
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2006 2 Effective Self-Training For Parsing
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2006 3 Alignment By Agreement
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2006 4 Improved Statistical Machine Translation Using Paraphrases
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2006 5 Learning For Semantic Parsing With Statistical Machine Translation
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2006 6 Exploiting Semantic Role Labeling, WordNet And Wikipedia For Coreference Resolution
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2006 7 Preemptive Information Extraction Using Unrestricted Relation Discovery
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2006 8 Arabic Preprocessing Schemes For Statistical Machine Translation
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2006 9 Identifying And Analyzing Judgment Opinions
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2006 10 Paraphrasing For Automatic Evaluation
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2006 11 Prototype-Driven Learning For Sequence Models
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2006 12 Integrating Probabilistic Extraction Models And Data Mining To Discover Relations And Patterns In Text
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2006 13 Parser Combination By Reparsing
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2006 14 Learning To Recognize Features Of Valid Textual Entailments
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2006 15 Synchronous Binarization For Machine Translation
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2004 1 Evaluating Content Selection In Summarization: The Pyramid Method
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2004 2 What’s In A Translation Rule?
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2004 3 Shallow Semantic Parsing Using Support Vector Machines
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2004 4 Catching The Drift: Probabilistic Content Models, With Applications To Generation And Summarization
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2004 5 Minimum Bayes-Risk Decoding For Statistical Machine Translation
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2004 6 A Smorgasbord Of Features For Statistical Machine Translation
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2004 7 Accurate Information Extraction From Research Papers Using Conditional Random Fields
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2004 8 Name Tagging With Word Clusters And Discriminative Training
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2004 9 Lattice-Based Search For Spoken Utterance Retrieval
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2004 10 A Statistical Model For Multilingual Entity Detection And Tracking
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2004 11 A Language Modeling Approach To Predicting Reading Difficulty
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2004 12 Automatically Labeling Semantic Classes
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2004 13 Training Tree Transducers
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2004 14 Improvements In Phrase-Based Statistical Machine Translation
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2004 15 Discriminative Reranking For Machine Translation
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2003 1 Statistical Phrase-Based Translation
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2003 2 Feature-Rich Part-of-Speech Tagging With A Cyclic Dependency Network
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2003 3 Automatic Evaluation Of Summaries Using N-gram Co-occurrence Statistics
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2003 4 Shallow Parsing With Conditional Random Fields
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2003 5 Learning To Paraphrase: An Unsupervised Approach Using Multiple-Sequence Alignment
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2003 6 Sentence Level Discourse Parsing Using Syntactic And Lexical Information
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2003 7 Factored Language Models And Generalized Parallel Backoff
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2003 8 Example Selection For Bootstrapping Statistical Parsers
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2003 9 Syntax-based Alignment Of Multiple Translations: Extracting Paraphrases And Generating New Sentences
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2003 10 Precision And Recall Of Machine Translation
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2003 11 Frequency Estimates For Statistical Word Similarity Measures
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2003 12 A* Parsing: Fast Exact Viterbi Parse Selection
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2003 13 COGEX: A Logic Prover For Question Answering
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2003 14 Learning Semantic Constraints For The Automatic Discovery Of Part-Whole Relations
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2003 15 Japanese Named Entity Extraction With Redundant Morphological Analysis
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2001 1 A Probabilistic Earley Parser As A Psycholinguistic Model
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2001 2 Chunking With Support Vector Machines
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 Taku Kudo; Yuji Matsumoto;
2001 3 Inducing Multilingual POS Taggers And NP Bracketers Via Robust Projection Across Aligned Corpora
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 David Yarowsky; Grace Ngai;
2001 4 Transformation Based Learning In The Fast Lane
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 Grace Ngai; Radu Florian;
2001 5 Multipath Translation Lexicon Induction Via Bridge Languages
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 Gideon S. Mann; David Yarowsky;
2001 6 Edit Detection And Parsing For Transcribed Speech
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 Eugene Charniak; Mark Johnson;
2001 7 Applying Co-Training Methods To Statistical Parsing
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 Anoop Sarkar;
2001 8 A Decision Tree Of Bigrams Is An Accurate Predictor Of Word Sense
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 Ted Pedersen;
2001 9 Knowledge-Free Induction Of Inflectional Morphologies
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 Patrick Schone; Daniel Jurafsky;
2001 10 Class-Based Probability Estimation Using A Semantic Hierarchy
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 Stephen Clark; David Weir;
2001 11 SPoT: A Trainable Sentence Planner
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 Marilyn A. Walker; Owen Rambow; Monica Rogati;
2001 12 Why Inverse Document Frequency?
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 Kishore Papineni;
2001 13 Text And Knowledge Mining For Coreference Resolution
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 Sanda M. Harabagiu; Razvan C. Bunescu; Steven J. Maiorano;
2001 14 Identifying Cognates By Phonetic And Semantic Similarity
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 Grzegorz Kondrak;
2001 15 Instance-Based Natural Language Generation
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 Sebastian Varges; Chris Mellish;
2000 1 A Maximum-Entropy-Inspired Parser
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 Eugene Charniak;
2000 2 Advances In Domain Independent Linear Text Segmentation
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 Freddy Y. Y. Choi;
2000 3 Cut And Paste Based Text Summarization
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 Hongyan Jing; Kathleen R. McKeown;
2000 4 A Novel Use Of Statistical Parsing To Extract Information From Text
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 Scott Miller; Heidi Fox; Lance Ramshaw; Ralph Weischedel;
2000 5 A New Algorithm For The Alignment Of Phonetic Sequences
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 Grzegorz Kondrak;
2000 6 A Simple Approach To Building Ensembles Of Naive Bayesian Classifiers For Word Sense Disambiguation
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 Ted Pedersen;
2000 7 Forest-Based Statistical Sentence Generation
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 Irene Langkilde;
2000 8 An Unsupervised Method For Detecting Grammatical Errors
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 Martin Chodorow; Claudia Leacock;
2000 9 Trainable Methods For Surface Natural Language Generation
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 Adwait Ratnaparkhi;
2000 10 Assigning Function Tags To Parsed Text
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 Don Blaheta; Eugene Charniak;
2000 11 Modelling Grounding And Discourse Obligations Using Update Rules
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 Colin Matheson; Massimo Poesio; David Traum;
2000 12 Morphological Tagging: Data Vs. Dictionaries
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 Jan Hajic;
2000 13 Learning To Predict Problematic Situations In A Spoken Dialogue System: Experiments With How May I Help You?
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 Marilyn Walker; Irene Langkilde; Jerry Wright; Allen Gorin; Diane Litman;
2000 14 The FrameNet Tagset For Frame-semantic And Syntactic Coding Of Predicate-argument Structure
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 Christopher Johnson; Charles J. Fillmore;
2000 15 Predicting Automatic Speech Recognition Performance Using Prosodic Cues
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 Diane J. Litman; Julia B. Hirschberg; Marc Swerts;