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# Works of Transactions of the Association for Computational Linguistics (TACL)

132 works · page 1 of 2 · the most cited first · [← Transactions of the Association for Computational…](https://md.research.elamur.ai/free/en/venues/tacl/)

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1. [**Natural Questions: A Benchmark for Question Answering Research**Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, et al.*2019 · 4,031 citations*](https://md.research.elamur.ai/free/en/papers/kwiatkowski-2019-natural-questions-benchmark-question-answering/)
2. [**SpanBERT: Improving Pre-training by Representing and Predicting Spans**Mandar Joshi, Danqi Chen, Yinhan Liu, et al.*2019 · 2,580 citations*](https://md.research.elamur.ai/free/en/papers/joshi-2019-spanbert-improving-pre-training-representing/)
3. [**Lost in the Middle: How Language Models Use Long Contexts**Nelson F. Liu, Kevin Lin, John Hewitt, et al.*2023 · 2,540 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-lost-middle-language-models-use/)
4. [**Named Entity Recognition with Bidirectional LSTM-CNNs**Jason P. C. Chiu, Eric Nichols*2015 · 2,276 citations*](https://md.research.elamur.ai/free/en/papers/chiu-2015-named-entity-recognition-bidirectional-lstm/)
5. [**Enriching Word Vectors with Subword Information**Piotr Bojanowski, Edouard Grave, Armand Joulin, et al.*2017 · 2,218 citations*](https://md.research.elamur.ai/free/en/papers/bojanowski-2017-enriching-word-vectors-subword-information/)
6. [**A Primer in BERTology: What We Know About How BERT Works**Anna Rogers, Olga Kovaleva, Anna Rumshisky*2020 · 2,127 citations*](https://md.research.elamur.ai/free/en/papers/rogers-2020-primer-bertology-what-we-know/)
7. [**CoQA: A Conversational Question Answering Challenge**Siva Reddy, Danqi Chen, Christopher D. Manning*2019 · 1,541 citations*](https://md.research.elamur.ai/free/en/papers/reddy-2019-coqa-conversational-question-answering-challenge/)
8. [**How Can We Know What Language Models Know?**Zhengbao Jiang, Frank F. Xu, Jun Araki, et al.*2020 · 1,493 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2020-how-can-we-know-what/)
9. [**Assessing the Ability of LSTMs to Learn Syntax-Sensitive Dependencies**Tal Linzen, Emmanuel Dupoux, Yoav Goldberg*2016 · 1,239 citations*](https://md.research.elamur.ai/free/en/papers/linzen-2016-assessing-ability-lstms-learn-syntax/)
10. [**ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs**Wenpeng Yin, Hinrich Schütze, Bing Xiang, et al.*2016 · 1,048 citations*](https://md.research.elamur.ai/free/en/papers/yin-2016-abcnn-attention-based-convolutional-neural/)
11. [**The NarrativeQA Reading Comprehension Challenge**Tomáš Kočiský, Jonathan Schwarz, Phil Blunsom, et al.*2018 · 1,026 citations*](https://md.research.elamur.ai/free/en/papers/kocisky-2018-narrativeqa-reading-comprehension-challenge/)
12. [**Optimizing Statistical Machine Translation for Text Simplification**Wei Xu, Courtney Napoles, Ellie Pavlick, et al.*2016 · 952 citations*](https://md.research.elamur.ai/free/en/papers/xu-2016-optimizing-statistical-machine-translation-text/)
13. [**Topic Modeling in Embedding Spaces**Adji B. Dieng, Francisco J. R. Ruiz, David M. Blei*2020 · 914 citations*](https://md.research.elamur.ai/free/en/papers/dieng-2020-topic-modeling-embedding-spaces/)
14. [**Grounded Compositional Semantics for Finding and Describing Images with Sentences**Richard Socher, Andrej Karpathy, Quoc V. Le, et al.*2014 · 909 citations*](https://md.research.elamur.ai/free/en/papers/socher-2014-grounded-compositional-semantics-finding-describing/)
15. [**Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations**Eliyahu Kiperwasser, Yoav Goldberg*2016 · 903 citations*](https://md.research.elamur.ai/free/en/papers/kiperwasser-2016-simple-accurate-dependency-parsing-bidirectional/)
16. [**What BERT Is Not: Lessons from a New Suite of Psycholinguistic Diagnostics for Language Models**Allyson Ettinger*2020 · 843 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2020-what-bert-is-not-lessons/)
17. [**Analysis Methods in Neural Language Processing: A Survey**Yonatan Belinkov, James Glass*2019 · 735 citations*](https://md.research.elamur.ai/free/en/papers/belinkov-2019-analysis-methods-neural-language-processing/)
18. [**TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages**Jonathan H. Clark, Eunsol Choi, Michael Collins, et al.*2020 · 691 citations*](https://md.research.elamur.ai/free/en/papers/clark-2020-tydi-qa-benchmark-information-seeking/)
19. [**Benchmarking Large Language Models for News Summarization**Tianyi Zhang, Faisal Ladhak, Esin Durmus, et al.*2024 · 663 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-benchmarking-large-language-models-news/)
20. [**Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation**Markus Freitag, George Foster, David Grangier, et al.*2021 · 660 citations*](https://md.research.elamur.ai/free/en/papers/freitag-2021-experts-errors-context-large-scale/)
21. [**Efficient Content-Based Sparse Attention with Routing Transformers**Aurko Roy, Mohammad Saffar, Ashish Vaswani, et al.*2020 · 660 citations*](https://md.research.elamur.ai/free/en/papers/roy-2020-efficient-content-based-sparse-attention/)
22. [**Problems in Current Text Simplification Research: New Data Can Help**Wei Xu, Chris Callison-Burch, Courtney Napoles*2015 · 659 citations*](https://md.research.elamur.ai/free/en/papers/xu-2015-problems-current-text-simplification-research/)
23. [**A Survey on Automated Fact-Checking**Zhijiang Guo, Michael Schlichtkrull, Andreas Vlachos*2022 · 646 citations*](https://md.research.elamur.ai/free/en/papers/guo-2022-survey-automated-fact-checking/)
24. [**Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond**Mikel Artetxe, Holger Schwenk*2018 · 627 citations*](https://md.research.elamur.ai/free/en/papers/artetxe-2018-massively-multilingual-sentence-embeddings-zero/)
25. [**Weakly Supervised Learning of Semantic Parsers for Mapping Instructions to Actions**Yoav Artzi, Luke Zettlemoyer*2013 · 592 citations*](https://md.research.elamur.ai/free/en/papers/artzi-2013-weakly-supervised-learning-semantic-parsers/)
26. [**Leveraging Pre-trained Checkpoints for Sequence Generation Tasks**Sascha Rothe, Shashi Narayan, Aliaksei Severyn*2019 · 562 citations*](https://md.research.elamur.ai/free/en/papers/rothe-2019-leveraging-pre-trained-checkpoints-sequence/)
27. [**Cross-Sentence N-ary Relation Extraction with Graph LSTMs**Nanyun Peng, Hoifung Poon, Chris Quirk, et al.*2017 · 553 citations*](https://md.research.elamur.ai/free/en/papers/peng-2017-cross-sentence-n-ary-relation/)
28. [**Fully Character-Level Neural Machine Translation without Explicit Segmentation**Jason Lee, Kyunghyun Cho, Thomas Hofmann*2017 · 545 citations*](https://md.research.elamur.ai/free/en/papers/lee-2017-fully-character-level-neural-machine/)
29. [**Sparse, Dense, and Attentional Representations for Text Retrieval**Yi Luan, Jacob Eisenstein, Kristina Toutanova, et al.*2021 · 500 citations*](https://md.research.elamur.ai/free/en/papers/luan-2021-sparse-dense-attentional-representations-text/)
30. [**Inherent Disagreements in Human Textual Inferences**Ellie Pavlick, Tom Kwiatkowski*2019 · 451 citations*](https://md.research.elamur.ai/free/en/papers/pavlick-2019-inherent-disagreements-human-textual-inferences/)
31. [**Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets**Julia Kreutzer, Isaac Caswell, Lisa Wang, et al.*2021 · 447 citations*](https://md.research.elamur.ai/free/en/papers/kreutzer-2021-quality-glance-audit-web-crawled/)
32. [**oLMpics — On what Language Model Pre-training Captures**Alon Talmor, Yanai Elazar, Yoav Goldberg, et al.*2019 · 432 citations*](https://md.research.elamur.ai/free/en/papers/talmor-2019-olmpics-language-model-pre-training/)
33. [**MasakhaNER: Named Entity Recognition for African Languages**David Ifeoluwa Adelani, Jade Abbott, Graham Neubig, et al.*2021 · 429 citations*](https://md.research.elamur.ai/free/en/papers/adelani-2021-masakhaner-named-entity-recognition-african/)
34. [**Dealing with Disagreements: Looking Beyond the Majority Vote in Subjective Annotations**Aida Mostafazadeh Davani, Mark Díaz, Vinodkumar Prabhakaran*2022 · 415 citations*](https://md.research.elamur.ai/free/en/papers/davani-2022-dealing-disagreements-looking-beyond-majority/)
35. [**Generating Sentences by Editing Prototypes**Kelvin Guu, Tatsunori B. Hashimoto, Yonatan Oren, et al.*2017 · 404 citations*](https://md.research.elamur.ai/free/en/papers/guu-2017-generating-sentences-editing-prototypes/)
36. [**Improving the Domain Adaptation of Retrieval Augmented Generation (RAG) Models for Open Domain Question Answering**Shamane Siriwardhana, Rivindu Weerasekera, Elliott Wen, et al.*2023 · 403 citations*](https://md.research.elamur.ai/free/en/papers/siriwardhana-2023-improving-domain-adaptation-retrieval-augmented/)
37. [**Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification**Xilun Chen, Yu Sun, Ben Athiwaratkun, et al.*2018 · 393 citations*](https://md.research.elamur.ai/free/en/papers/chen-2018-adversarial-deep-averaging-networks-cross/)
38. [**♫ MuSiQue: Multihop Questions via Single-hop Question Composition**Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, et al.*2022 · 384 citations*](https://md.research.elamur.ai/free/en/papers/trivedi-2022-musique-multihop-questions-single-hop/)
39. [**Many Languages, One Parser**Waleed Ammar, George Mulcaire, Miguel Ballesteros, et al.*2016 · 382 citations*](https://md.research.elamur.ai/free/en/papers/ammar-2016-many-languages-one-parser/)
40. [**A Survey on Model Compression for Large Language Models**Xunyu Zhu, Jian Li, Yong Liu, et al.*2024 · 381 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2024-survey-model-compression-large-language/)
41. [**From Paraphrase Database to Compositional Paraphrase Model and Back**John Wieting, Mohit Bansal, Kevin Gimpel, et al.*2015 · 375 citations*](https://md.research.elamur.ai/free/en/papers/wieting-2015-paraphrase-database-compositional-paraphrase-model/)
42. [**A Latent Variable Model Approach to PMI-based Word Embeddings**Sanjeev Arora, Yuanzhi Li, Yingyu Liang, et al.*2016 · 365 citations*](https://md.research.elamur.ai/free/en/papers/arora-2016-latent-variable-model-approach-pmi/)
43. [**Mind the GAP: A Balanced Corpus of Gendered Ambiguous Pronouns**Kellie Webster, Marta Recasens, Vera Axelrod, et al.*2018 · 358 citations*](https://md.research.elamur.ai/free/en/papers/webster-2018-mind-gap-balanced-corpus-gendered/)
44. [**Temporal Annotation in the Clinical Domain**William F. Styler IV, Steven Bethard, Sean Finan, et al.*2014 · 349 citations*](https://md.research.elamur.ai/free/en/papers/iv-2014-temporal-annotation-clinical-domain/)
45. [**xCOMET: Transparent Machine Translation Evaluation through Fine-grained Error Detection**Nuno M. Guerreiro, Ricardo Rei, Daan van Stigt, et al.*2024 · 333 citations*](https://md.research.elamur.ai/free/en/papers/guerreiro-2024-xcomet-transparent-machine-translation-evaluation/)
46. [**DREAM: A Challenge Data Set and Models for Dialogue-Based Reading Comprehension**Kai Sun, Dian Yu, Jianshu Chen, et al.*2019 · 331 citations*](https://md.research.elamur.ai/free/en/papers/sun-2019-dream-challenge-data-set-models/)
47. [**A Joint Model for Entity Analysis: Coreference, Typing, and Linking**Greg Durrett, Dan Klein*2014 · 329 citations*](https://md.research.elamur.ai/free/en/papers/durrett-2014-joint-model-entity-analysis-coreference/)
48. [**Improving Distributional Similarity with Lessons Learned from Word Embeddings**Omer Levy, Yoav Goldberg, Ido Dagan*2015 · 313 citations*](https://md.research.elamur.ai/free/en/papers/levy-2015-improving-distributional-similarity-lessons-learned/)
49. [**Measuring the Evolution of a Scientific Field through Citation Frames**David Jurgens, Srijan Kumar, Raine Hoover, et al.*2018 · 311 citations*](https://md.research.elamur.ai/free/en/papers/jurgens-2018-measuring-evolution-scientific-field-through/)
50. [**Gender Bias in Machine Translation**Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, et al.*2021 · 310 citations*](https://md.research.elamur.ai/free/en/papers/savoldi-2021-gender-bias-machine-translation/)
51. [**Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages**Gowtham Ramesh, Sumanth Doddapaneni, Aravinth Bheemaraj, et al.*2022 · 307 citations*](https://md.research.elamur.ai/free/en/papers/ramesh-2022-samanantar-largest-publicly-available-parallel/)
52. [**PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them**Patrick Lewis, Yuxiang Wu, Linqing Liu, et al.*2021 · 286 citations*](https://md.research.elamur.ai/free/en/papers/lewis-2021-paq-65-million-probably-asked/)
53. [**Constructing Datasets for Multi-hop Reading Comprehension Across Documents**Johannes Welbl, Pontus Stenetorp, Sebastian Riedel*2018 · 283 citations*](https://md.research.elamur.ai/free/en/papers/welbl-2018-constructing-datasets-multi-hop-reading/)
54. [**An Empirical Survey of Data Augmentation for Limited Data Learning in NLP**Jiaao Chen, Derek Tam, Colin Raffel, et al.*2023 · 253 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-empirical-survey-data-augmentation-limited/)
55. [**Linear Algebraic Structure of Word Senses, with Applications to Polysemy**Sanjeev Arora, Yuanzhi Li, Yingyu Liang, et al.*2018 · 247 citations*](https://md.research.elamur.ai/free/en/papers/arora-2018-linear-algebraic-structure-word-senses/)
56. [**Hallucinations in Large Multilingual Translation Models**Nuno M. Guerreiro, Duarte M. Alves, Jonas Waldendorf, et al.*2023 · 244 citations*](https://md.research.elamur.ai/free/en/papers/guerreiro-2023-hallucinations-large-multilingual-translation-models/)
57. [**Amnesic Probing: Behavioral Explanation with Amnesic Counterfactuals**Yanai Elazar, Shauli Ravfogel, Alon Jacovi, et al.*2021 · 241 citations*](https://md.research.elamur.ai/free/en/papers/elazar-2021-amnesic-probing-behavioral-explanation-amnesic/)
58. [**The Benefits of a Model of Annotation**Rebecca J. Passonneau, Bob Carpenter*2014 · 238 citations*](https://md.research.elamur.ai/free/en/papers/passonneau-2014-benefits-model-annotation/)
59. [**FeTaQA: Free-form Table Question Answering**Linyong Nan, Chiachun Hsieh, Ziming Mao, et al.*2022 · 234 citations*](https://md.research.elamur.ai/free/en/papers/nan-2022-fetaqa-free-form-table-question/)
60. [**Learning to Understand Phrases by Embedding the Dictionary**Felix Hill, Kyunghyun Cho, Anna Korhonen, et al.*2016 · 234 citations*](https://md.research.elamur.ai/free/en/papers/hill-2016-learning-understand-phrases-embedding-dictionary/)
61. [**Break It Down: A Question Understanding Benchmark**Tomer Wolfson, Mor Geva, Ankit Gupta, et al.*2020 · 218 citations*](https://md.research.elamur.ai/free/en/papers/wolfson-2020-break-it-down-question-understanding/)
62. [**An Empirical Analysis of Formality in Online Communication**Ellie Pavlick, Joel Tetreault*2016 · 215 citations*](https://md.research.elamur.ai/free/en/papers/pavlick-2016-empirical-analysis-formality-online-communication/)
63. [**Why Does Surprisal From Larger Transformer-Based Language Models Provide a Poorer Fit to Human Reading Times?**Byung-Doh Oh, William Schuler*2023 · 211 citations*](https://md.research.elamur.ai/free/en/papers/oh-2023-why-does-surprisal-larger-transformer/)
64. [**Exploring Human-Like Translation Strategy with Large Language Models**Zhiwei He, Tian Liang, Wenxiang Jiao, et al.*2024 · 207 citations*](https://md.research.elamur.ai/free/en/papers/he-2024-exploring-human-like-translation-strategy/)
65. [**One Vector is Not Enough: Entity-Augmented Distributed Semantics for Discourse Relations**Yangfeng Ji, Jacob Eisenstein*2015 · 198 citations*](https://md.research.elamur.ai/free/en/papers/ji-2015-one-vector-is-not-enough/)
66. [**Multilingual Projection for Parsing Truly Low-Resource Languages**Željko Agić, Anders Johannsen, Barbara Plank, et al.*2016 · 195 citations*](https://md.research.elamur.ai/free/en/papers/agic-2016-multilingual-projection-parsing-truly-low/)
67. [**Time-Aware Language Models as Temporal Knowledge Bases**Bhuwan Dhingra, Jeremy R. Cole, Julian Martin Eisenschlos, et al.*2022 · 194 citations*](https://md.research.elamur.ai/free/en/papers/dhingra-2022-time-aware-language-models-as/)
68. [**Ordinal Common-sense Inference**Sheng Zhang, Rachel Rudinger, Kevin Duh, et al.*2017 · 192 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2017-ordinal-common-sense-inference/)
69. [**Entity Linking meets Word Sense Disambiguation: a Unified Approach**Andrea Moro, Alessandro Raganato, Roberto Navigli*2014 · 188 citations*](https://md.research.elamur.ai/free/en/papers/moro-2014-entity-linking-meets-word-sense/)
70. [**Planning with Learned Entity Prompts for Abstractive Summarization**Shashi Narayan, Yao Zhao, Joshua Maynez, et al.*2021 · 180 citations*](https://md.research.elamur.ai/free/en/papers/narayan-2021-planning-learned-entity-prompts-abstractive/)
71. [**On Generative Spoken Language Modeling from Raw Audio**Kushal Lakhotia, Eugene Kharitonov, Wei-Ning Hsu, et al.*2021 · 165 citations*](https://md.research.elamur.ai/free/en/papers/lakhotia-2021-generative-spoken-language-modeling-raw/)
72. [**When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs**Ryo Kamoi, Yusen Zhang, Nan Zhang, et al.*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/kamoi-2024-when-can-llms-actually-correct/)
73. [**Semantic Neural Machine Translation Using AMR**Linfeng Song, Daniel Gildea, Yue Zhang, et al.*2019 · 159 citations*](https://md.research.elamur.ai/free/en/papers/song-2019-semantic-neural-machine-translation-amr/)
74. [**Discriminative Lexical Semantic Segmentation with Gaps: Running the MWE Gamut**Nathan Schneider, Emily Danchik, Chris Dyer, et al.*2014 · 159 citations*](https://md.research.elamur.ai/free/en/papers/schneider-2014-discriminative-lexical-semantic-segmentation-gaps/)
75. [**Testing the Predictions of Surprisal Theory in 11 Languages**Ethan G. Wilcox, Tiago Pimentel, Clara Meister, et al.*2023 · 158 citations*](https://md.research.elamur.ai/free/en/papers/wilcox-2023-testing-predictions-surprisal-theory-11/)
76. [**Automatic Detection and Language Identification of Multilingual Documents**Marco Lui, Jey Han Lau, Timothy Baldwin*2014 · 157 citations*](https://md.research.elamur.ai/free/en/papers/lui-2014-automatic-detection-language-identification-multilingual/)
77. [**Canine: Pre-training an Efficient Tokenization-Free Encoder for Language Representation**Jonathan H. Clark, Dan Garrette, Iulia Turc, et al.*2022 · 156 citations*](https://md.research.elamur.ai/free/en/papers/clark-2022-canine-pre-training-efficient-tokenization/)
78. [**Colors in Context: A Pragmatic Neural Model for Grounded Language Understanding**Will Monroe, Robert X.D. Hawkins, Noah D. Goodman, et al.*2017 · 155 citations*](https://md.research.elamur.ai/free/en/papers/monroe-2017-colors-context-pragmatic-neural-model/)
79. [**Unsupervised Quality Estimation for Neural Machine Translation**Marina Fomicheva, Shuo Sun, Lisa Yankovskaya, et al.*2020 · 153 citations*](https://md.research.elamur.ai/free/en/papers/fomicheva-2020-unsupervised-quality-estimation-neural-machine/)
80. [**Locally Typical Sampling**Clara Meister, Tiago Pimentel, Gian Wiher, et al.*2023 · 152 citations*](https://md.research.elamur.ai/free/en/papers/meister-2023-locally-typical-sampling/)
81. [**MIRACL: A Multilingual Retrieval Dataset Covering 18 Diverse Languages**Xinyu Zhang, Nandan Thakur, Odunayo Ogundepo, et al.*2023 · 148 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-miracl-multilingual-retrieval-dataset-covering/)
82. [**Mapping to Declarative Knowledge for Word Problem Solving**Subhro Roy, Dan Roth*2018 · 143 citations*](https://md.research.elamur.ai/free/en/papers/roy-2018-mapping-declarative-knowledge-word-problem/)
83. [**Syntax-Guided Controlled Generation of Paraphrases**Ashutosh Kumar, Kabir Ahuja, Raghuram Vadapalli, et al.*2020 · 131 citations*](https://md.research.elamur.ai/free/en/papers/kumar-2020-syntax-guided-controlled-generation-paraphrases/)
84. [**Scheduled Multi-Task Learning: From Syntax to Translation**Eliyahu Kiperwasser, Miguel Ballesteros*2018 · 130 citations*](https://md.research.elamur.ai/free/en/papers/kiperwasser-2018-scheduled-multi-task-learning-syntax/)
85. [**Still a Pain in the Neck: Evaluating Text Representations on Lexical Composition**Vered Shwartz, Ido Dagan*2019 · 129 citations*](https://md.research.elamur.ai/free/en/papers/shwartz-2019-still-pain-neck-evaluating-text/)
86. [**Does Syntax Need to Grow on Trees? Sources of Hierarchical Inductive Bias in Sequence-to-Sequence Networks**R. Thomas McCoy, Robert Frank, Tal Linzen*2020 · 122 citations*](https://md.research.elamur.ai/free/en/papers/mccoy-2020-does-syntax-need-grow-trees/)
87. [**High Quality Rather than High Model Probability: Minimum Bayes Risk Decoding with Neural Metrics**Markus Freitag, David Grangier, Qijun Tan, et al.*2022 · 120 citations*](https://md.research.elamur.ai/free/en/papers/freitag-2022-high-quality-rather-than-high/)
88. [**Task-Oriented Dialogue as Dataflow Synthesis**Jacob Andreas, John Bufe, David Burkett, et al.*2020 · 119 citations*](https://md.research.elamur.ai/free/en/papers/andreas-2020-task-oriented-dialogue-as-dataflow/)
89. [**Latent Structures for Coreference Resolution**Sebastian Martschat, Michael Strube*2015 · 111 citations*](https://md.research.elamur.ai/free/en/papers/martschat-2015-latent-structures-coreference-resolution/)
90. [**AMR-To-Text Generation with Graph Transformer**Tianming Wang, Xiaojun Wan, Hanqi Jin*2020 · 108 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-amr-text-generation-graph-transformer/)
91. [**Investigating Reasons for Disagreement in Natural Language Inference**Nan-Jiang Jiang, Marie-Catherine de Marneffe*2022 · 104 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2022-investigating-reasons-disagreement-natural-language/)
92. [**Measuring Machine Translation Errors in New Domains**Ann Irvine, John Morgan, Marine Carpuat, et al.*2013 · 104 citations*](https://md.research.elamur.ai/free/en/papers/irvine-2013-measuring-machine-translation-errors-new/)
93. [**In-Order Transition-based Constituent Parsing**Jiangming Liu, Yue Zhang*2017 · 98 citations*](https://md.research.elamur.ai/free/en/papers/liu-2017-order-transition-based-constituent-parsing/)
94. [**The Galactic Dependencies Treebanks: Getting More Data by Synthesizing New Languages**Dingquan Wang, Jason Eisner*2016 · 98 citations*](https://md.research.elamur.ai/free/en/papers/wang-2016-galactic-dependencies-treebanks-getting-more/)
95. [**Minimally-Supervised Morphological Segmentation using Adaptor Grammars**Kairit Sirts, Sharon Goldwater*2013 · 94 citations*](https://md.research.elamur.ai/free/en/papers/sirts-2013-minimally-supervised-morphological-segmentation-adaptor/)
96. [**It's not Rocket Science: Interpreting Figurative Language in Narratives**Tuhin Chakrabarty, Yejin Choi, Vered Shwartz*2022 · 91 citations*](https://md.research.elamur.ai/free/en/papers/chakrabarty-2022-it-s-not-rocket-science/)
97. [**Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation**Patrick Fernandes, Aman Madaan, Emmy Liu, et al.*2023 · 84 citations*](https://md.research.elamur.ai/free/en/papers/fernandes-2023-bridging-gap-survey-integrating-human/)
98. [**Language Modeling for Morphologically Rich Languages: Character-Aware Modeling for Word-Level Prediction**Daniela Gerz, Ivan Vulić, Edoardo Ponti, et al.*2018 · 82 citations*](https://md.research.elamur.ai/free/en/papers/gerz-2018-language-modeling-morphologically-rich-languages/)
99. [**Coreference Resolution through a seq2seq Transition-Based System**Bernd Bohnet, Chris Alberti, Michael Collins*2023 · 77 citations*](https://md.research.elamur.ai/free/en/papers/bohnet-2023-coreference-resolution-through-seq2seq-transition/)
100. [**Idiomatic Expression Identification using Semantic Compatibility**Ziheng Zeng, Suma Bhat*2021 · 75 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2021-idiomatic-expression-identification-semantic-compatibility/)

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