---
title: "Conference on Empirical Methods in Natural… — works, page 3"
description: "703 works of Conference on Empirical Methods in Natural Language Processing (EMNLP) in our library · page 3 of 8, the most cited first."
canonical: "https://research.elamur.ai/free/en/venues/emnlp/works/page/3/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/venues/emnlp/works/page/3/)

[home](https://md.research.elamur.ai/free/en/) / [venues](https://md.research.elamur.ai/free/en/venues/) / [Conference on Empirical Methods in Natural…](https://md.research.elamur.ai/free/en/venues/emnlp/) / [works](https://md.research.elamur.ai/free/en/venues/emnlp/works/) / page 3

# Works of Conference on Empirical Methods in Natural Language Processing (EMNLP)

703 works · page 3 of 8 · the most cited first · [← Conference on Empirical Methods in Natural…](https://md.research.elamur.ai/free/en/venues/emnlp/)

[← prev](https://md.research.elamur.ai/free/en/venues/emnlp/works/page/2/) [1](https://md.research.elamur.ai/free/en/venues/emnlp/works/) [2](https://md.research.elamur.ai/free/en/venues/emnlp/works/page/2/) **3** [4](https://md.research.elamur.ai/free/en/venues/emnlp/works/page/4/) … [8](https://md.research.elamur.ai/free/en/venues/emnlp/works/page/8/) [next →](https://md.research.elamur.ai/free/en/venues/emnlp/works/page/4/)

201. [**LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models**Zhiqiang Hu, Lei Wang, Yihuai Lan, et al.*2023 · 398 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-llm-adapters-adapter-family-parameter/)
202. [**Automatic Prompt Optimization with “Gradient Descent” and Beam Search**Reid Pryzant, Dan Iter, Jerry Li, et al.*2023 · 397 citations*](https://md.research.elamur.ai/free/en/papers/pryzant-2023-automatic-prompt-optimization-gradient-descent/)
203. [**Literal and Metaphorical Sense Identification through Concrete and Abstract Context**Peter Turney, Yair Neuman, Dan Assaf, et al.*2011 · 394 citations*](https://md.research.elamur.ai/free/en/papers/turney-2011-literal-metaphorical-sense-identification-through/)
204. [**A Challenge Dataset and Effective Models for Aspect-Based Sentiment Analysis**Qingnan Jiang, Lei Chen, Ruifeng Xu, et al.*2019 · 393 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2019-challenge-dataset-effective-models-aspect/)
205. [**That's So Annoying!!!: A Lexical and Frame-Semantic Embedding Based Data Augmentation Approach to Automatic Categorization of Annoying Behaviors using #petpeeve Tweets**William Yang Wang, Diyi Yang*2015 · 391 citations*](https://md.research.elamur.ai/free/en/papers/wang-2015-that-s-so-annoying-lexical/)
206. [**Tuning as Ranking**Mark Hopkins, Jonathan May*2011 · 391 citations*](https://md.research.elamur.ai/free/en/papers/hopkins-2011-tuning-as-ranking/)
207. [**Cheap and Fast – But is it Good? Evaluating Non-Expert Annotations for Natural Language Tasks**Rion Snow, Brendan O'Connor, Daniel Jurafsky, et al.*2008 · 390 citations*](https://md.research.elamur.ai/free/en/papers/snow-2008-cheap-fast-but-is-it/)
208. [**DeClarE: Debunking Fake News and False Claims using Evidence-Aware Deep Learning**Kashyap Popat, Subhabrata Mukherjee, Andrew Yates, et al.*2018 · 388 citations*](https://md.research.elamur.ai/free/en/papers/popat-2018-declare-debunking-fake-news-false/)
209. [**A Stack-Propagation Framework with Token-Level Intent Detection for Spoken Language Understanding**Libo Qin, Wanxiang Che, Yangming Li, et al.*2019 · 384 citations*](https://md.research.elamur.ai/free/en/papers/qin-2019-stack-propagation-framework-token-level/)
210. [**Query Rewriting in Retrieval-Augmented Large Language Models**Xinbei Ma, Yeyun Gong, Pengcheng He, et al.*2023 · 383 citations*](https://md.research.elamur.ai/free/en/papers/ma-2023-query-rewriting-retrieval-augmented-large/)
211. [**Fine-Grained Analysis of Propaganda in News Articles**Giovanni Da San Martino, Seunghak Yu, Alberto Barrón-Cedeño, et al.*2019 · 379 citations*](https://md.research.elamur.ai/free/en/papers/martino-2019-fine-grained-analysis-propaganda-news/)
212. [**ETC: Encoding Long and Structured Inputs in Transformers**Joshua Ainslie, Santiago Ontañón, Chris Alberti, et al.*2020 · 377 citations*](https://md.research.elamur.ai/free/en/papers/ainslie-2020-etc-encoding-long-structured-inputs/)
213. [**Paragraph-level Neural Question Generation with Maxout Pointer and Gated Self-attention Networks**Yao Zhao, Xiaochuan Ni, Yuanyuan Ding, et al.*2018 · 376 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2018-paragraph-level-neural-question-generation/)
214. [**Chinese Poetry Generation with Recurrent Neural Networks**Xingxing Zhang, Mirella Lapata*2014 · 376 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2014-chinese-poetry-generation-recurrent-neural/)
215. [**Position-Aware Tagging for Aspect Sentiment Triplet Extraction**Lu Xu, Hao Li, Wei Lu, et al.*2020 · 370 citations*](https://md.research.elamur.ai/free/en/papers/xu-2020-position-aware-tagging-aspect-sentiment/)
216. [**Knowledge-Enriched Transformer for Emotion Detection in Textual Conversations**Peixiang Zhong, Di Wang, Chunyan Miao*2019 · 370 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2019-knowledge-enriched-transformer-emotion-detection/)
217. [**Question Generation for Question Answering**Nan Duan, Duyu Tang, Peng Chen, et al.*2017 · 370 citations*](https://md.research.elamur.ai/free/en/papers/duan-2017-question-generation-question-answering/)
218. [**Improving the Transformer Translation Model with Document-Level Context**Jiacheng Zhang, Huanbo Luan, Maosong Sun, et al.*2018 · 368 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2018-improving-transformer-translation-model-document/)
219. [**The “Problem” of Human Label Variation: On Ground Truth in Data, Modeling and Evaluation**Barbara Plank*2022 · 364 citations*](https://md.research.elamur.ai/free/en/papers/plank-2022-problem-human-label-variation-ground/)
220. [**Latent Hatred: A Benchmark for Understanding Implicit Hate Speech**Mai ElSherief, Caleb Ziems, David Muchlinski, et al.*2021 · 364 citations*](https://md.research.elamur.ai/free/en/papers/elsherief-2021-latent-hatred-benchmark-understanding-implicit/)
221. [**GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge**Luyao Huang, Chi Sun, Xipeng Qiu, et al.*2019 · 364 citations*](https://md.research.elamur.ai/free/en/papers/huang-2019-glossbert-bert-word-sense-disambiguation/)
222. [**A Transition-Based System for Joint Part-of-Speech Tagging and Labeled Non-Projective Dependency Parsing**Bernd Bohnet, Joakim Nivre*2012 · 364 citations*](https://md.research.elamur.ai/free/en/papers/bohnet-2012-transition-based-system-joint-part/)
223. [**The FLORES Evaluation Datasets for Low-Resource Machine Translation: Nepali–English and Sinhala–English**Francisco Guzmán, Peng-Jen Chen, Myle Ott, et al.*2019 · 361 citations*](https://md.research.elamur.ai/free/en/papers/guzman-2019-flores-evaluation-datasets-low-resource/)
224. [**How Much Reading Does Reading Comprehension Require? A Critical Investigation of Popular Benchmarks**Divyansh Kaushik, Zachary C. Lipton*2018 · 361 citations*](https://md.research.elamur.ai/free/en/papers/kaushik-2018-how-much-reading-does-reading/)
225. [**TOD-BERT: Pre-trained Natural Language Understanding for Task-Oriented Dialogue**Chien-Sheng Wu, Steven C.H. Hoi, Richard Socher, et al.*2020 · 360 citations*](https://md.research.elamur.ai/free/en/papers/wu-2020-tod-bert-pre-trained-natural/)
226. [**Analyzing the Behavior of Visual Question Answering Models**Aishwarya Agrawal, Dhruv Batra, Devi Parikh*2016 · 358 citations*](https://md.research.elamur.ai/free/en/papers/agrawal-2016-analyzing-behavior-visual-question-answering/)
227. [**A Unified Model for Word Sense Representation and Disambiguation**Xinxiong Chen, Zhiyuan Liu, Maosong Sun*2014 · 358 citations*](https://md.research.elamur.ai/free/en/papers/chen-2014-unified-model-word-sense-representation/)
228. [**Experiments with a Higher-Order Projective Dependency Parser**Xavier Carreras*2007 · 358 citations*](https://md.research.elamur.ai/free/en/papers/carreras-2007-experiments-higher-order-projective-dependency/)
229. [**Adversarial Removal of Demographic Attributes from Text Data**Yanai Elazar, Yoav Goldberg*2018 · 357 citations*](https://md.research.elamur.ai/free/en/papers/elazar-2018-adversarial-removal-demographic-attributes-text/)
230. [**XGLUE: A New Benchmark Dataset for Cross-lingual Pre-training, Understanding and Generation**Yaobo Liang, Nan Duan, Yeyun Gong, et al.*2020 · 356 citations*](https://md.research.elamur.ai/free/en/papers/liang-2020-xglue-new-benchmark-dataset-cross/)
231. [**Query2doc: Query Expansion with Large Language Models**Liang Wang, Nan Yang, Furu Wei*2023 · 353 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-query2doc-query-expansion-large-language/)
232. [**QuestEval: Summarization Asks for Fact-based Evaluation**Thomas Scialom, Paul-Alexis Dray, Sylvain Lamprier, et al.*2021 · 353 citations*](https://md.research.elamur.ai/free/en/papers/scialom-2021-questeval-summarization-asks-fact-based/)
233. [**Understanding the Value of Features for Coreference Resolution**Eric Bengtson, Dan Roth*2008 · 352 citations*](https://md.research.elamur.ai/free/en/papers/bengtson-2008-understanding-value-features-coreference-resolution/)
234. [**Zero-Resource Translation with Multi-Lingual Neural Machine Translation**Orhan Firat, Baskaran Sankaran, Yaser Al-onaizan, et al.*2016 · 350 citations*](https://md.research.elamur.ai/free/en/papers/firat-2016-zero-resource-translation-multi-lingual/)
235. [**Reformulating Unsupervised Style Transfer as Paraphrase Generation**Kalpesh Krishna, John Wieting, Mohit Iyyer*2020 · 348 citations*](https://md.research.elamur.ai/free/en/papers/krishna-2020-reformulating-unsupervised-style-transfer-as/)
236. [**Do NLP Models Know Numbers? Probing Numeracy in Embeddings**Eric Wallace, Yizhong Wang, Sujian Li, et al.*2019 · 348 citations*](https://md.research.elamur.ai/free/en/papers/wallace-2019-do-nlp-models-know-numbers/)
237. [**Unsupervised Semantic Parsing**Hoifung Poon, Pedro Domingos*2009 · 345 citations*](https://md.research.elamur.ai/free/en/papers/poon-2009-unsupervised-semantic-parsing/)
238. [**Lessons from Natural Language Inference in the Clinical Domain**Alexey Romanov, Chaitanya Shivade*2018 · 343 citations*](https://md.research.elamur.ai/free/en/papers/romanov-2018-lessons-natural-language-inference-clinical/)
239. [**Transformer Feed-Forward Layers Build Predictions by Promoting Concepts in the Vocabulary Space**Mor Geva, Avi Caciularu, Kevin Ro Wang, et al.*2022 · 342 citations*](https://md.research.elamur.ai/free/en/papers/geva-2022-transformer-feed-forward-layers-build/)
240. [**Deep Learning for Chinese Word Segmentation and POS Tagging**Xiaoqing Zheng, Hanyang Chen, Tianyu Xu*2013 · 340 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2013-deep-learning-chinese-word-segmentation/)
241. [**Information-Theoretic Probing with Minimum Description Length**Elena Voita, Ivan Titov*2020 · 339 citations*](https://md.research.elamur.ai/free/en/papers/voita-2020-information-theoretic-probing-minimum-description/)
242. [**Sentence Compression by Deletion with LSTMs**Katja Filippova, Enrique Alfonseca, Carlos A. Colmenares, et al.*2015 · 337 citations*](https://md.research.elamur.ai/free/en/papers/filippova-2015-sentence-compression-deletion-lstms/)
243. [**Certified Robustness to Adversarial Word Substitutions**Robin Jia, Aditi Raghunathan, Kerem Göksel, et al.*2019 · 336 citations*](https://md.research.elamur.ai/free/en/papers/jia-2019-certified-robustness-adversarial-word-substitutions/)
244. [**A Tale of Two Parsers: Investigating and Combining Graph-based and Transition-based Dependency Parsing**Yue Zhang, Stephen Clark*2008 · 336 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2008-tale-two-parsers-investigating-combining/)
245. [**LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models**Huiqiang Jiang, Qianhui Wu, Chin-Yew Lin, et al.*2023 · 335 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2023-llmlingua-compressing-prompts-accelerated-inference/)
246. [**Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT**Akshay Smit, Saahil Jain, Pranav Rajpurkar, et al.*2020 · 334 citations*](https://md.research.elamur.ai/free/en/papers/smit-2020-combining-automatic-labelers-expert-annotations/)
247. [**Predicting Factuality of Reporting and Bias of News Media Sources**Ramy Baly, Georgi Karadzhov, Dimitar Alexandrov, et al.*2018 · 334 citations*](https://md.research.elamur.ai/free/en/papers/baly-2018-predicting-factuality-reporting-bias-news/)
248. [**Training Millions of Personalized Dialogue Agents**Pierre-Emmanuel Mazaré, Samuel Humeau, Martin Raison, et al.*2018 · 334 citations*](https://md.research.elamur.ai/free/en/papers/mazare-2018-training-millions-personalized-dialogue-agents/)
249. [**Learning to Simplify Sentences with Quasi-Synchronous Grammar and Integer Programming**Kristian Woodsend, Mirella Lapata*2011 · 334 citations*](https://md.research.elamur.ai/free/en/papers/woodsend-2011-learning-simplify-sentences-quasi-synchronous/)
250. [**RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning**Mingkai Deng, Jianyu Wang, Cheng-Ping Hsieh, et al.*2022 · 327 citations*](https://md.research.elamur.ai/free/en/papers/deng-2022-rlprompt-optimizing-discrete-text-prompts/)
251. [**Aspect Sentiment Quad Prediction as Paraphrase Generation**Wenxuan Zhang, Yang Deng, Xin Li, et al.*2021 · 325 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2021-aspect-sentiment-quad-prediction-as/)
252. [**A Dataset for Document Grounded Conversations**Kangyan Zhou, Shrimai Prabhumoye, Alan W Black*2018 · 324 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2018-dataset-document-grounded-conversations/)
253. [**Cultural Shift or Linguistic Drift? Comparing Two Computational Measures of Semantic Change**William L. Hamilton, Jure Leskovec, Dan Jurafsky*2016 · 324 citations*](https://md.research.elamur.ai/free/en/papers/hamilton-2016-cultural-shift-or-linguistic-drift/)
254. [**Controlling Output Length in Neural Encoder-Decoders**Yuta Kikuchi, Graham Neubig, Ryohei Sasano, et al.*2016 · 323 citations*](https://md.research.elamur.ai/free/en/papers/kikuchi-2016-controlling-output-length-neural-encoder/)
255. [**Question-Answer Driven Semantic Role Labeling: Using Natural Language to Annotate Natural Language**Luheng He, Mike Lewis, Luke Zettlemoyer*2015 · 322 citations*](https://md.research.elamur.ai/free/en/papers/he-2015-question-answer-driven-semantic-role/)
256. [**Probing Pretrained Language Models for Lexical Semantics**Ivan Vulić, Edoardo Maria Ponti, Robert Litschko, et al.*2020 · 320 citations*](https://md.research.elamur.ai/free/en/papers/vulic-2020-probing-pretrained-language-models-lexical/)
257. [**Rapid Adaptation of Neural Machine Translation to New Languages**Graham Neubig, Junjie Hu*2018 · 320 citations*](https://md.research.elamur.ai/free/en/papers/neubig-2018-rapid-adaptation-neural-machine-translation/)
258. [**A Comparison of Vector-based Representations for Semantic Composition**William Blacoe, Mirella Lapata*2012 · 320 citations*](https://md.research.elamur.ai/free/en/papers/blacoe-2012-comparison-vector-based-representations-semantic/)
259. [**MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims**Isabelle Augenstein, Christina Lioma, Dongsheng Wang, et al.*2019 · 318 citations*](https://md.research.elamur.ai/free/en/papers/augenstein-2019-multifc-real-world-multi-domain/)
260. [**SimVerb-3500: A Large-Scale Evaluation Set of Verb Similarity**Daniela Gerz, Ivan Vulić, Felix Hill, et al.*2016 · 315 citations*](https://md.research.elamur.ai/free/en/papers/gerz-2016-simverb-3500-large-scale-evaluation/)
261. [**Explainable Automated Fact-Checking for Public Health Claims**Neema Kotonya, Francesca Toni*2020 · 314 citations*](https://md.research.elamur.ai/free/en/papers/kotonya-2020-explainable-automated-fact-checking-public/)
262. [**Decoding with Large-Scale Neural Language Models Improves Translation**Ashish Vaswani, Yinggong Zhao, Victoria Fossum, et al.*2013 · 314 citations*](https://md.research.elamur.ai/free/en/papers/vaswani-2013-decoding-large-scale-neural-language/)
263. [**Chinese Syntactic Reordering for Statistical Machine Translation**Chao Wang, Michael Collins, Philipp Koehn*2007 · 314 citations*](https://md.research.elamur.ai/free/en/papers/wang-2007-chinese-syntactic-reordering-statistical-machine/)
264. [**Unsupervised Pretraining for Sequence to Sequence Learning**Prajit Ramachandran, Peter Liu, Quoc Le*2017 · 312 citations*](https://md.research.elamur.ai/free/en/papers/ramachandran-2017-unsupervised-pretraining-sequence-sequence-learning/)
265. [**Dependency Parsing and Domain Adaptation with LR Models and Parser Ensembles**Kenji Sagae, Jun'ichi Tsujii*2007 · 311 citations*](https://md.research.elamur.ai/free/en/papers/sagae-2007-dependency-parsing-domain-adaptation-lr/)
266. [**Get out the vote: Determining support or opposition from Congressional floor-debate transcripts**Matt Thomas, Bo Pang, Lillian Lee*2006 · 307 citations*](https://md.research.elamur.ai/free/en/papers/thomas-2006-get-out-vote-determining-support/)
267. [**Discriminative Instance Weighting for Domain Adaptation in Statistical Machine Translation**George Foster, Cyril Goutte, Roland Kuhn*2010 · 305 citations*](https://md.research.elamur.ai/free/en/papers/foster-2010-discriminative-instance-weighting-domain-adaptation/)
268. [**Multi-passage BERT: A Globally Normalized BERT Model for Open-domain Question Answering**Zhiguo Wang, Patrick Ng, Xiaofei Ma, et al.*2019 · 304 citations*](https://md.research.elamur.ai/free/en/papers/wang-2019-multi-passage-bert-globally-normalized/)
269. [**An Empirical Evaluation of Knowledge Sources and Learning Algorithms for Word Sense Disambiguation**Yoong Keok Lee, Hwee Tou Ng*2002 · 302 citations*](https://md.research.elamur.ai/free/en/papers/lee-2002-empirical-evaluation-knowledge-sources-learning/)
270. [**MoEL: Mixture of Empathetic Listeners**Zhaojiang Lin, Andrea Madotto, Jamin Shin, et al.*2019 · 301 citations*](https://md.research.elamur.ai/free/en/papers/lin-2019-moel-mixture-empathetic-listeners/)
271. [**Learning Named Entity Tagger using Domain-Specific Dictionary**Jingbo Shang, Liyuan Liu, Xiaotao Gu, et al.*2018 · 301 citations*](https://md.research.elamur.ai/free/en/papers/shang-2018-learning-named-entity-tagger-domain/)
272. [**Globally Coherent Text Generation with Neural Checklist Models**Chloé Kiddon, Luke Zettlemoyer, Yejin Choi*2016 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kiddon-2016-globally-coherent-text-generation-neural/)
273. [**Character-LLM: A Trainable Agent for Role-Playing**Yunfan Shao, Linyang Li, Junqi Dai, et al.*2023 · 300 citations*](https://md.research.elamur.ai/free/en/papers/shao-2023-character-llm-trainable-agent-role/)
274. [**Improving Translation Quality by Discarding Most of the Phrasetable**Howard Johnson, Joel Martin, George Foster, et al.*2007 · 300 citations*](https://md.research.elamur.ai/free/en/papers/johnson-2007-improving-translation-quality-discarding-most/)
275. [**Muppet: Massive Multi-task Representations with Pre-Finetuning**Armen Aghajanyan, Anchit Gupta, Akshat Shrivastava, et al.*2021 · 299 citations*](https://md.research.elamur.ai/free/en/papers/aghajanyan-2021-muppet-massive-multi-task-representations/)
276. [**Paraphrase Generation with Deep Reinforcement Learning**Zichao Li, Xin Jiang, Lifeng Shang, et al.*2018 · 298 citations*](https://md.research.elamur.ai/free/en/papers/li-2018-paraphrase-generation-deep-reinforcement-learning/)
277. [**Incorporating Discrete Translation Lexicons into Neural Machine Translation**Philip Arthur, Graham Neubig, Satoshi Nakamura*2016 · 298 citations*](https://md.research.elamur.ai/free/en/papers/arthur-2016-incorporating-discrete-translation-lexicons-into/)
278. [**A Dependency Parser for Tweets**Lingpeng Kong, Nathan Schneider, Swabha Swayamdipta, et al.*2014 · 298 citations*](https://md.research.elamur.ai/free/en/papers/kong-2014-dependency-parser-tweets/)
279. [**Towards Debiasing Fact Verification Models**Tal Schuster, Darsh Shah, Yun Jie Serene Yeo, et al.*2019 · 296 citations*](https://md.research.elamur.ai/free/en/papers/schuster-2019-debiasing-fact-verification-models/)
280. [**Show Me Your Evidence - an Automatic Method for Context Dependent Evidence Detection**Ruty Rinott, Lena Dankin, Carlos Alzate Perez, et al.*2015 · 296 citations*](https://md.research.elamur.ai/free/en/papers/rinott-2015-show-me-your-evidence-automatic/)
281. [**Document-Level Machine Translation with Large Language Models**Longyue Wang, Chenyang Lyu, Tianbo Ji, et al.*2023 · 295 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-document-level-machine-translation-large/)
282. [**Entity-Based Knowledge Conflicts in Question Answering**Shayne Longpre, Kartik Perisetla, Anthony Chen, et al.*2021 · 295 citations*](https://md.research.elamur.ai/free/en/papers/longpre-2021-entity-based-knowledge-conflicts-question/)
283. [**Scalable Multi-Hop Relational Reasoning for Knowledge-Aware Question Answering**Yanlin Feng, Xinyue Chen, Bill Yuchen Lin, et al.*2020 · 295 citations*](https://md.research.elamur.ai/free/en/papers/feng-2020-scalable-multi-hop-relational-reasoning/)
284. [**Broad-Coverage Sense Disambiguation and Information Extraction with a Supersense Sequence Tagger**Massimiliano Ciaramita, Yasemin Altun*2006 · 295 citations*](https://md.research.elamur.ai/free/en/papers/ciaramita-2006-broad-coverage-sense-disambiguation-information/)
285. [**Baize: An Open-Source Chat Model with Parameter-Efficient Tuning on Self-Chat Data**Canwen Xu, Daya Guo, Nan Duan, et al.*2023 · 294 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-baize-open-source-chat-model/)
286. [**AdapterDrop: On the Efficiency of Adapters in Transformers**Andreas Rücklé, Gregor Geigle, Max Glockner, et al.*2021 · 294 citations*](https://md.research.elamur.ai/free/en/papers/ruckle-2021-adapterdrop-efficiency-adapters-transformers/)
287. [**Easy Victories and Uphill Battles in Coreference Resolution**Greg Durrett, Dan Klein*2013 · 293 citations*](https://md.research.elamur.ai/free/en/papers/durrett-2013-easy-victories-uphill-battles-coreference/)
288. [**Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little**Koustuv Sinha, Robin Jia, Dieuwke Hupkes, et al.*2021 · 292 citations*](https://md.research.elamur.ai/free/en/papers/sinha-2021-masked-language-modeling-distributional-hypothesis/)
289. [**Simple and Effective Few-Shot Named Entity Recognition with Structured Nearest Neighbor Learning**Yi Yang, Arzoo Katiyar*2020 · 291 citations*](https://md.research.elamur.ai/free/en/papers/yang-2020-simple-effective-few-shot-named/)
290. [**Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human Attack**Emily Dinan, Samuel Humeau, Bharath Chintagunta, et al.*2019 · 291 citations*](https://md.research.elamur.ai/free/en/papers/dinan-2019-build-it-break-it-fix/)
291. [**Exploiting Cross-Sentence Context for Neural Machine Translation**Longyue Wang, Zhaopeng Tu, Andy Way, et al.*2017 · 291 citations*](https://md.research.elamur.ai/free/en/papers/wang-2017-exploiting-cross-sentence-context-neural/)
292. [**A Benchmark Dataset for Learning to Intervene in Online Hate Speech**Jing Qian, Anna Bethke, Yinyin Liu, et al.*2019 · 290 citations*](https://md.research.elamur.ai/free/en/papers/qian-2019-benchmark-dataset-learning-intervene-online/)
293. [**Modeling Biological Processes for Reading Comprehension**Jonathan Berant, Vivek Srikumar, Pei-Chun Chen, et al.*2014 · 288 citations*](https://md.research.elamur.ai/free/en/papers/berant-2014-modeling-biological-processes-reading-comprehension/)
294. [**SwitchOut: an Efficient Data Augmentation Algorithm for Neural Machine Translation**Xinyi Wang, Hieu Pham, Zihang Dai, et al.*2018 · 287 citations*](https://md.research.elamur.ai/free/en/papers/wang-2018-switchout-efficient-data-augmentation-algorithm/)
295. [**Why We Need New Evaluation Metrics for NLG**Jekaterina Novikova, Ondřej Dušek, Amanda Cercas Curry, et al.*2017 · 287 citations*](https://md.research.elamur.ai/free/en/papers/novikova-2017-why-we-need-new-evaluation/)
296. [**Two are Better than One: Joint Entity and Relation Extraction with Table-Sequence Encoders**Jue Wang, Wei Lu*2020 · 286 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-two-are-better-than-one/)
297. [**emrQA: A Large Corpus for Question Answering on Electronic Medical Records**Anusri Pampari, Preethi Raghavan, Jennifer Liang, et al.*2018 · 285 citations*](https://md.research.elamur.ai/free/en/papers/pampari-2018-emrqa-large-corpus-question-answering/)
298. [**Learning to Paraphrase for Question Answering**Li Dong, Jonathan Mallinson, Siva Reddy, et al.*2017 · 285 citations*](https://md.research.elamur.ai/free/en/papers/dong-2017-learning-paraphrase-question-answering/)
299. [**Lexical Generalization in CCG Grammar Induction for Semantic Parsing**Tom Kwiatkowski, Luke Zettlemoyer, Sharon Goldwater, et al.*2011 · 283 citations*](https://md.research.elamur.ai/free/en/papers/kwiatkowski-2011-lexical-generalization-ccg-grammar-induction/)
300. [**API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs**Minghao Li, Yingxiu Zhao, Bowen Yu, et al.*2023 · 281 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-api-bank-comprehensive-benchmark-tool/)

[← prev](https://md.research.elamur.ai/free/en/venues/emnlp/works/page/2/) [1](https://md.research.elamur.ai/free/en/venues/emnlp/works/) [2](https://md.research.elamur.ai/free/en/venues/emnlp/works/page/2/) **3** [4](https://md.research.elamur.ai/free/en/venues/emnlp/works/page/4/) … [8](https://md.research.elamur.ai/free/en/venues/emnlp/works/page/8/) [next →](https://md.research.elamur.ai/free/en/venues/emnlp/works/page/4/)

- [← back to](https://md.research.elamur.ai/free/en/venues/emnlp/) — Conference on Empirical Methods in Natural Language Processing (EMNLP)