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title: "Findings of the Association for Computational Linguistics"
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# Findings of the Association for Computational Linguistics 2020 — accepted papers

Findings of the Association for Computational Linguistics 2020 is the 2020 edition of the Findings of the Association for Computational Linguistics, held in Online, November 2020 (publisher: Association for Computational Linguistics). The ACL Anthology lists 447 papers of it; our library holds 41 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

[**447** papers in the proceedings](#all) · [**41** works in our library](https://md.research.elamur.ai/free/en/venues/findings/2020/works/) · [**14,028** citations of these works](https://md.research.elamur.ai/free/en/venues/findings/2020/works/)**Online** where it was held**November 2020** when

## Most cited papers

By their OpenAlex citations; a paper with our summary links to its page here, the others to the original.

1. **[CodeBERT: A Pre-Trained Model for Programming and Natural Languages](https://md.research.elamur.ai/free/en/papers/feng-2020-codebert-pre-trained-model-programming/)**Zhangyin Feng, Daya Guo, Duyu Tang et al.*2,679 citations · our summary*
2. **[TinyBERT: Distilling BERT for Natural Language Understanding](https://aclanthology.org/2020.findings-emnlp.372/)**Xiaoqi Jiao, Yichun Yin, Lifeng Shang et al.*1,729 citations*
3. **[LEGAL-BERT: The Muppets straight out of Law School](https://md.research.elamur.ai/free/en/papers/chalkidis-2020-legal-bert-muppets-straight-out/)**Ilias Chalkidis, Manos Fergadiotis, Prodromos Malakasiotis et al.*994 citations · our summary*
4. **[TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classification](https://md.research.elamur.ai/free/en/papers/barbieri-2020-tweeteval-unified-benchmark-comparative-evaluation/)**Francesco Barbieri, Jose Camacho-Collados, Luis Espinosa Anke et al.*674 citations · our summary*
5. **[RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models](https://md.research.elamur.ai/free/en/papers/gehman-2020-realtoxicityprompts-evaluating-neural-toxic-degeneration/)**Samuel Gehman, Suchin Gururangan, Maarten Sap et al.*654 citations · our summary*
6. **[Revisiting Pre-Trained Models for Chinese Natural Language Processing](https://md.research.elamur.ai/free/en/papers/cui-2020-revisiting-pre-trained-models-chinese/)**Yiming Cui, Wanxiang Che, Ting Liu et al.*578 citations · our summary*
7. **[UNIFIEDQA: Crossing Format Boundaries with a Single QA System](https://md.research.elamur.ai/free/en/papers/khashabi-2020-unifiedqa-crossing-format-boundaries-single/)**Daniel Khashabi, Sewon Min, Tushar Khot et al.*489 citations · our summary*
8. **[PhoBERT: Pre-trained language models for Vietnamese](https://md.research.elamur.ai/free/en/papers/nguyen-2020-phobert-pre-trained-language-models/)**Dat Quoc Nguyen, Anh Tuan Nguyen*456 citations · our summary*
9. **[Document Ranking with a Pretrained Sequence-to-Sequence Model](https://md.research.elamur.ai/free/en/papers/nogueira-2020-document-ranking-pretrained-sequence-sequence/)**Rodrigo Nogueira, Zhiying Jiang, Ronak Pradeep et al.*448 citations · our summary*
10. **[IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual Language Models for Indian Languages](https://md.research.elamur.ai/free/en/papers/kakwani-2020-indicnlpsuite-monolingual-corpora-evaluation-benchmarks/)**Divyanshu Kakwani, Anoop Kunchukuttan, Satish Golla et al.*446 citations · our summary*

## All accepted papers (447)

The most cited first; 41 with our summary link to their page here, the others to the original.

1. **[CodeBERT: A Pre-Trained Model for Programming and Natural Languages](https://md.research.elamur.ai/free/en/papers/feng-2020-codebert-pre-trained-model-programming/)**Zhangyin Feng, Daya Guo, Duyu Tang et al.*2,679 citations · our summary*
2. **[TinyBERT: Distilling BERT for Natural Language Understanding](https://aclanthology.org/2020.findings-emnlp.372/)**Xiaoqi Jiao, Yichun Yin, Lifeng Shang et al.*1,729 citations*
3. **[LEGAL-BERT: The Muppets straight out of Law School](https://md.research.elamur.ai/free/en/papers/chalkidis-2020-legal-bert-muppets-straight-out/)**Ilias Chalkidis, Manos Fergadiotis, Prodromos Malakasiotis et al.*994 citations · our summary*
4. **[TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classification](https://md.research.elamur.ai/free/en/papers/barbieri-2020-tweeteval-unified-benchmark-comparative-evaluation/)**Francesco Barbieri, Jose Camacho-Collados, Luis Espinosa Anke et al.*674 citations · our summary*
5. **[RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models](https://md.research.elamur.ai/free/en/papers/gehman-2020-realtoxicityprompts-evaluating-neural-toxic-degeneration/)**Samuel Gehman, Suchin Gururangan, Maarten Sap et al.*654 citations · our summary*
6. **[Revisiting Pre-Trained Models for Chinese Natural Language Processing](https://md.research.elamur.ai/free/en/papers/cui-2020-revisiting-pre-trained-models-chinese/)**Yiming Cui, Wanxiang Che, Ting Liu et al.*578 citations · our summary*
7. **[UNIFIEDQA: Crossing Format Boundaries with a Single QA System](https://md.research.elamur.ai/free/en/papers/khashabi-2020-unifiedqa-crossing-format-boundaries-single/)**Daniel Khashabi, Sewon Min, Tushar Khot et al.*489 citations · our summary*
8. **[PhoBERT: Pre-trained language models for Vietnamese](https://md.research.elamur.ai/free/en/papers/nguyen-2020-phobert-pre-trained-language-models/)**Dat Quoc Nguyen, Anh Tuan Nguyen*456 citations · our summary*
9. **[Document Ranking with a Pretrained Sequence-to-Sequence Model](https://md.research.elamur.ai/free/en/papers/nogueira-2020-document-ranking-pretrained-sequence-sequence/)**Rodrigo Nogueira, Zhiying Jiang, Ronak Pradeep et al.*448 citations · our summary*
10. **[IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual Language Models for Indian Languages](https://md.research.elamur.ai/free/en/papers/kakwani-2020-indicnlpsuite-monolingual-corpora-evaluation-benchmarks/)**Divyanshu Kakwani, Anoop Kunchukuttan, Satish Golla et al.*446 citations · our summary*
11. **[ProphetNet: Predicting Future N-gram for Sequence-to-SequencePre-training](https://md.research.elamur.ai/free/en/papers/qi-2020-prophetnet-predicting-future-n-gram/)**Weizhen Qi, Yu Yan, Yeyun Gong et al.*374 citations · our summary*
12. **[COSMIC: COmmonSense knowledge for eMotion Identification in Conversations](https://aclanthology.org/2020.findings-emnlp.224/)**Deepanway Ghosal, Navonil Majumder, Alexander Gelbukh et al.*361 citations*
13. **[Evaluating Models' Local Decision Boundaries via Contrast Sets](https://md.research.elamur.ai/free/en/papers/gardner-2020-evaluating-models-local-decision-boundaries/)**Matt Gardner, Yoav Artzi, Victoria Basmov et al.*256 citations · our summary*
14. **[RobBERT: a Dutch RoBERTa-based Language Model](https://md.research.elamur.ai/free/en/papers/delobelle-2020-robbert-dutch-roberta-based-language/)**Pieter Delobelle, Thomas Winters, Bettina Berendt*235 citations · our summary*
15. **[CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning](https://aclanthology.org/2020.findings-emnlp.165/)**Bill Yuchen Lin, Wangchunshu Zhou, Ming Shen et al.*231 citations*
16. **[Grid Tagging Scheme for Aspect-oriented Fine-grained Opinion Extraction](https://aclanthology.org/2020.findings-emnlp.234/)**Zhen Wu, Chengcan Ying, Fei Zhao et al.*225 citations*
17. **[HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data](https://md.research.elamur.ai/free/en/papers/chen-2020-hybridqa-dataset-multi-hop-question/)**Wenhu Chen, Hanwen Zha, Zhiyu Chen et al.*201 citations · our summary*
18. **[Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages](https://md.research.elamur.ai/free/en/papers/nekoto-2020-participatory-research-low-resourced-machine/)**Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila et al.*182 citations · our summary*
19. **[Bridging Textual and Tabular Data for Cross-Domain Text-to-SQL Semantic Parsing](https://md.research.elamur.ai/free/en/papers/lin-2020-bridging-textual-tabular-data-cross/)**Xi Victoria Lin, Richard Socher, Caiming Xiong*181 citations · our summary*
20. **[ConveRT: Efficient and Accurate Conversational Representations from Transformers](https://md.research.elamur.ai/free/en/papers/henderson-2020-convert-efficient-accurate-conversational-representations/)**Matthew Henderson, Iñigo Casanueva, Nikola Mrkšić et al.*176 citations · our summary*
21. **[Event Extraction as Multi-turn Question Answering](https://md.research.elamur.ai/free/en/papers/li-2020-event-extraction-as-multi-turn/)**Fayuan Li, Weihua Peng, Yuguang Chen et al.*173 citations · our summary*
22. **[Byte Pair Encoding is Suboptimal for Language Model Pretraining](https://md.research.elamur.ai/free/en/papers/bostrom-2020-byte-pair-encoding-is-suboptimal/)**Kaj Bostrom, Greg Durrett*172 citations · our summary*
23. **[Few-shot Natural Language Generation for Task-Oriented Dialog](https://md.research.elamur.ai/free/en/papers/peng-2020-few-shot-natural-language-generation/)**Baolin Peng, Chenguang Zhu, Chunyuan Li et al.*164 citations · our summary*
24. **[TLDR: Extreme Summarization of Scientific Documents](https://md.research.elamur.ai/free/en/papers/cachola-2020-tldr-extreme-summarization-scientific-documents/)**Isabel Cachola, Kyle Lo, Arman Cohan et al.*162 citations · our summary*
25. **[Blockwise Self-Attention for Long Document Understanding](https://aclanthology.org/2020.findings-emnlp.232/)**Jiezhong Qiu, Hao Ma, Omer Levy et al.*161 citations*

[See all 447 papers in Findings of the Association for Computational Linguistics 2020 — accepted papers →](https://md.research.elamur.ai/free/en/venues/findings/2020/papers/)

## Papers with our summary in our library (41)

The most cited first (OpenAlex citations plus our library's).

1. **[CodeBERT: A Pre-Trained Model for Programming and Natural Languages](https://md.research.elamur.ai/free/en/papers/feng-2020-codebert-pre-trained-model-programming/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhangyin Feng, Daya Guo, Duyu Tang, et al.*2020 · 2,960 citations*
2. **[LEGAL-BERT: The Muppets straight out of Law School](https://md.research.elamur.ai/free/en/papers/chalkidis-2020-legal-bert-muppets-straight-out/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ilias Chalkidis, Manos Fergadiotis, Prodromos Malakasiotis, et al.*2020 · 1,493 citations*
3. **[RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models](https://md.research.elamur.ai/free/en/papers/gehman-2020-realtoxicityprompts-evaluating-neural-toxic-degeneration/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Samuel Gehman, Suchin Gururangan, Maarten Sap, et al.*2020 · 1,281 citations*
4. **[UNIFIEDQA: Crossing Format Boundaries with a Single QA System](https://md.research.elamur.ai/free/en/papers/khashabi-2020-unifiedqa-crossing-format-boundaries-single/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Daniel Khashabi, Sewon Min, Tushar Khot, et al.*2020 · 844 citations*
5. **[IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual Language Models for Indian Languages](https://md.research.elamur.ai/free/en/papers/kakwani-2020-indicnlpsuite-monolingual-corpora-evaluation-benchmarks/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Divyanshu Kakwani, Anoop Kunchukuttan, Satish Golla, et al.*2020 · 730 citations*
6. **[PhoBERT: Pre-trained language models for Vietnamese](https://md.research.elamur.ai/free/en/papers/nguyen-2020-phobert-pre-trained-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dat Quoc Nguyen, Anh Tuan Nguyen*2020 · 571 citations*
7. **[Document Ranking with a Pretrained Sequence-to-Sequence Model](https://md.research.elamur.ai/free/en/papers/nogueira-2020-document-ranking-pretrained-sequence-sequence/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rodrigo Nogueira, Zhiying Jiang, Ronak Pradeep, et al.*2020 · 540 citations*
8. [**Evaluating Models' Local Decision Boundaries via Contrast Sets**Matt Gardner, Yoav Artzi, Victoria Basmov, et al.*2020 · 522 citations*](https://md.research.elamur.ai/free/en/papers/gardner-2020-evaluating-models-local-decision-boundaries/)
9. **[ProphetNet: Predicting Future N-gram for Sequence-to-SequencePre-training](https://md.research.elamur.ai/free/en/papers/qi-2020-prophetnet-predicting-future-n-gram/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weizhen Qi, Yu Yan, Yeyun Gong, et al.*2020 · 453 citations*
10. **[Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages](https://md.research.elamur.ai/free/en/papers/nekoto-2020-participatory-research-low-resourced-machine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila, et al.*2020 · 334 citations*
11. **[Byte Pair Encoding is Suboptimal for Language Model Pretraining](https://md.research.elamur.ai/free/en/papers/bostrom-2020-byte-pair-encoding-is-suboptimal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaj Bostrom, Greg Durrett*2020 · 309 citations*
12. **[WikiLingua: A New Benchmark Dataset for Cross-Lingual Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/ladhak-2020-wikilingua-new-benchmark-dataset-cross/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Faisal Ladhak, Esin Durmus, Claire Cardie, et al.*2020 · 273 citations*
13. **[ConveRT: Efficient and Accurate Conversational Representations from Transformers](https://md.research.elamur.ai/free/en/papers/henderson-2020-convert-efficient-accurate-conversational-representations/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Matthew Henderson, Iñigo Casanueva, Nikola Mrkšić, et al.*2020 · 268 citations*
14. **[Bridging Textual and Tabular Data for Cross-Domain Text-to-SQL Semantic Parsing](https://md.research.elamur.ai/free/en/papers/lin-2020-bridging-textual-tabular-data-cross/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xi Victoria Lin, Richard Socher, Caiming Xiong*2020 · 261 citations*
15. **[TLDR: Extreme Summarization of Scientific Documents](https://md.research.elamur.ai/free/en/papers/cachola-2020-tldr-extreme-summarization-scientific-documents/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Isabel Cachola, Kyle Lo, Arman Cohan, et al.*2020 · 260 citations*
16. **[Few-shot Natural Language Generation for Task-Oriented Dialog](https://md.research.elamur.ai/free/en/papers/peng-2020-few-shot-natural-language-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Baolin Peng, Chenguang Zhu, Chunyuan Li, et al.*2020 · 255 citations*
17. **[Event Extraction as Multi-turn Question Answering](https://md.research.elamur.ai/free/en/papers/li-2020-event-extraction-as-multi-turn/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fayuan Li, Weihua Peng, Yuguang Chen, et al.*2020 · 250 citations*
18. **[HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verification](https://md.research.elamur.ai/free/en/papers/jiang-2020-hover-dataset-many-hop-fact/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yichen Jiang, Shikha Bordia, Zheng Zhong, et al.*2020 · 221 citations*
19. **[Evaluating Factuality in Generation with Dependency-level Entailment](https://md.research.elamur.ai/free/en/papers/goyal-2020-evaluating-factuality-generation-dependency-level/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tanya Goyal, Greg Durrett*2020 · 203 citations*
20. **[Generative Data Augmentation for Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2020-generative-data-augmentation-commonsense-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yiben Yang, Chaitanya Malaviya, Jared Fernandez, et al.*2020 · 195 citations*
21. **[Modeling Intra and Inter-modality Incongruity for Multi-Modal Sarcasm Detection](https://md.research.elamur.ai/free/en/papers/pan-2020-modeling-intra-inter-modality-incongruity/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hongliang Pan, Zheng Lin, Peng Fu, et al.*2020 · 181 citations*
22. **[Towards Controllable Biases in Language Generation](https://md.research.elamur.ai/free/en/papers/sheng-2020-controllable-biases-language-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Emily Sheng, Kai-Wei Chang, Prem Natarajan, et al.*2020 · 167 citations*
23. **[Understanding tables with intermediate pre-training](https://md.research.elamur.ai/free/en/papers/eisenschlos-2020-understanding-tables-intermediate-pre-training/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Julian Eisenschlos, Syrine Krichene, Thomas Müller*2020 · 158 citations*
24. **[Reducing Quantity Hallucinations in Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/zhao-2020-reducing-quantity-hallucinations-abstractive-summarization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zheng Zhao, Shay B. Cohen, Bonnie Webber*2020 · 156 citations*
25. **[Exploring Versatile Generative Language Model Via Parameter-Efficient Transfer Learning](https://md.research.elamur.ai/free/en/papers/lin-2020-exploring-versatile-generative-language-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhaojiang Lin, Andrea Madotto, Pascale Fung*2020 · 151 citations*

[See all 41 works in Findings of the Association for Computational Linguistics 2020 — accepted papers →](https://md.research.elamur.ai/free/en/venues/findings/2020/works/)

## Top topics

Topics of its works in our library, with the number of works on each.

[Language models & pretraining (7)](https://md.research.elamur.ai/free/en/topics/language-models/) · [Evaluation & benchmarks (5)](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Multilingual & cross-lingual NLP (4)](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/) · [Machine translation (3)](https://md.research.elamur.ai/free/en/topics/machine-translation/) · [Sentiment & emotion (3)](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · [Summarization (3)](https://md.research.elamur.ai/free/en/topics/summarization/) · [Hebrew & Aramaic (3)](https://md.research.elamur.ai/free/en/topics/hebrew-aramaic/) · [Semitic languages (3)](https://md.research.elamur.ai/free/en/topics/semitic-languages/) · [Question answering (2)](https://md.research.elamur.ai/free/en/topics/question-answering/) · [Text generation (2)](https://md.research.elamur.ai/free/en/topics/text-generation/) · [Dialogue systems (2)](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [Morphology (2)](https://md.research.elamur.ai/free/en/topics/morphology/) · [Reasoning (2)](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Code & programming languages (2)](https://md.research.elamur.ai/free/en/topics/code-and-programming/) · [Vision & language (2)](https://md.research.elamur.ai/free/en/topics/multimodal/)

**15 more topics**

[English (2)](https://md.research.elamur.ai/free/en/topics/english/) · [Modern Hebrew (2)](https://md.research.elamur.ai/free/en/topics/modern-hebrew/) · [Discourse analysis (1)](https://md.research.elamur.ai/free/en/topics/discourse-analysis/) · [Dependency parsing (1)](https://md.research.elamur.ai/free/en/topics/dependency-parsing/) · [Universal Dependencies (1)](https://md.research.elamur.ai/free/en/topics/universal-dependencies/) · [Treebanks (1)](https://md.research.elamur.ai/free/en/topics/treebanks/) · [Information extraction (1)](https://md.research.elamur.ai/free/en/topics/information-extraction/) · [Low-resource languages (1)](https://md.research.elamur.ai/free/en/topics/low-resource-languages/) · [Legal AI (1)](https://md.research.elamur.ai/free/en/topics/legal-ai/) · [Information retrieval & search (1)](https://md.research.elamur.ai/free/en/topics/information-retrieval/) · [Semantic parsing & meaning representation (1)](https://md.research.elamur.ai/free/en/topics/semantic-parsing/) · [Bias, fairness & safety (1)](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Tokenization & segmentation (1)](https://md.research.elamur.ai/free/en/topics/tokenization/) · [Idioms & multiword expressions (1)](https://md.research.elamur.ai/free/en/topics/multiword-expressions/) · [Biblical Hebrew (1)](https://md.research.elamur.ai/free/en/topics/biblical-hebrew/)

## Fields

[Computer Science (40)](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities (39)](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Social Sciences (7)](https://md.research.elamur.ai/free/en/shelves/social-sciences/) · [Psychology (1)](https://md.research.elamur.ai/free/en/shelves/psychology/)

## Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

[🧑‍🔬**Noah A. Smith**3 works here · 1,906 citations](https://md.research.elamur.ai/free/en/authors/noah-a-smith/) · [🧑‍🔬**Daniel Khashabi**3 works here · 1,511 citations](https://md.research.elamur.ai/free/en/authors/daniel-khashabi/) · [🧑‍🔬**Reut Tsarfaty**3 works here · 549 citations](https://md.research.elamur.ai/free/en/authors/reut-tsarfaty/) · [🧑‍🔬**Ming Zhou**2 works here · 3,413 citations](https://md.research.elamur.ai/free/en/authors/ming-zhou/) · [🧑‍🔬**Nan Duan**2 works here · 3,413 citations](https://md.research.elamur.ai/free/en/authors/nan-duan/) · [🧑‍🔬**Yejin Choi**2 works here · 1,476 citations](https://md.research.elamur.ai/free/en/authors/yejin-choi/) · [🧑‍🔬**Hannaneh Hajishirzi**2 works here · 1,366 citations](https://md.research.elamur.ai/free/en/authors/hannaneh-hajishirzi/) · [🧑‍🔬**Ashish Sabharwal**2 works here · 989 citations](https://md.research.elamur.ai/free/en/authors/ashish-sabharwal/) · [🧑‍🔬**Tushar Khot**2 works here · 989 citations](https://md.research.elamur.ai/free/en/authors/tushar-khot/) · [🧑‍🔬**Greg Durrett**2 works here · 512 citations](https://md.research.elamur.ai/free/en/authors/greg-durrett/) · [🧑‍🔬**Mohit Bansal**2 works here · 341 citations](https://md.research.elamur.ai/free/en/authors/mohit-bansal/) · [🧑‍🔬**Bing Qin**1 work here · 2,960 citations](https://md.research.elamur.ai/free/en/authors/bing-qin/)

## Top institutions

Institutions on the bylines of its works here, by the number of works.

[🔬**Allen Institute for Artificial Intelligence** Seattle · United States 7 works here](https://md.research.elamur.ai/free/en/labs/allen-institute-for-artificial-intelligence/) · [🎓**University of Washington** Seattle · United States 5 works here](https://md.research.elamur.ai/free/en/universities/university-of-washington/) · [🏢**Microsoft** Redmond · United States 3 works here](https://md.research.elamur.ai/free/en/companies/microsoft/) · [🏢**Google** Mountain View · United States 3 works here](https://md.research.elamur.ai/free/en/companies/google/) · [🎓**Bar-Ilan University** Ramat Gan · Israel 3 works here](https://md.research.elamur.ai/free/en/universities/bar-ilan-university/) · [🎓**University of Edinburgh** Edinburgh · United Kingdom 3 works here](https://md.research.elamur.ai/free/en/universities/university-of-edinburgh/) · [🎓**University of North Carolina at Chapel Hill** Chapel Hill · United States 2 works here](https://md.research.elamur.ai/free/en/universities/university-of-north-carolina-at-chapel-hill/) · [🎓**University of Southern California** Los Angeles · United States 2 works here](https://md.research.elamur.ai/free/en/universities/university-of-southern-california/) · [🎓**University of Waterloo** Waterloo · Canada 2 works here](https://md.research.elamur.ai/free/en/universities/university-of-waterloo/) · [🎓**Cornell University** Ithaca · United States 2 works here](https://md.research.elamur.ai/free/en/universities/cornell-university/) · [🎓**University of Cambridge** Cambridge · United Kingdom 2 works here](https://md.research.elamur.ai/free/en/universities/university-of-cambridge/) · [🏢**Microsoft Research Asia** Beijing · China 2 works here](https://md.research.elamur.ai/free/en/companies/microsoft-research-asia/)

Place and dates from the event's site or the ACL Anthology; works and citations from OpenAlex and our library.

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