---
title: "NAACL 2021 — accepted papers — Elamur Research"
description: "NAACL 2021 — accepted papers: 74 papers in the Elamur Research library (Online), with our summaries, ranked by citations."
canonical: "https://research.elamur.ai/free/en/venues/naacl/2021/"
---
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# NAACL 2021 — accepted papers

NAACL 2021 is the 2021 edition of the Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), held in Online, June 2021 (publisher: Association for Computational Linguistics). The ACL Anthology lists 560 papers of it in 5 tracks; our library holds 74 with our summaries. Below: its awards, the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

[**560** papers in the proceedings](#all) · [**74** works in our library](https://md.research.elamur.ai/free/en/venues/naacl/2021/works/) · [**19,165** citations of these works](https://md.research.elamur.ai/free/en/venues/naacl/2021/works/)**Online** where it was held**June 2021** when

## Tracks

Main 477Industry Papers 39Student Research Workshop 21Demonstrations 17Tutorials 6

## Awards

As the ACL Anthology records them.

1. **[It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners](https://md.research.elamur.ai/free/en/papers/schick-2021-it-s-not-just-size/)**Timo Schick, Hinrich Schütze · 🏆 Outstanding Long Paper*685 citations · our summary*
2. **[Learning How to Ask: Querying LMs with Mixtures of Soft Prompts](https://md.research.elamur.ai/free/en/papers/qin-2021-learning-ask-querying-lms-mixtures/)**Guanghui Qin, Jason Eisner · 🏆 Best Short Paper*328 citations · our summary*
3. **[How many data points is a prompt worth?](https://md.research.elamur.ai/free/en/papers/scao-2021-how-many-data-points-is/)**Teven Le Scao, Alexander Rush · 🏆 Outstanding Short Paper*179 citations · our summary*
4. **[COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation](https://aclanthology.org/2021.naacl-demos.8/)**Qingyun Wang, Manling Li, Xuan Wang et al. · Demonstrations · 🏆 Best Demo Paper*121 citations*
5. **[Unifying Cross-Lingual Semantic Role Labeling with Heterogeneous Linguistic Resources](https://aclanthology.org/2021.naacl-main.31/)**Simone Conia, Andrea Bacciu, Roberto Navigli · 🏆 Outstanding Long Paper*25 citations*
6. **[Video-aided Unsupervised Grammar Induction](https://aclanthology.org/2021.naacl-main.119/)**Songyang Zhang, Linfeng Song, Lifeng Jin et al. · 🏆 Best Long Paper*21 citations*
7. **[Preregistering NLP research](https://aclanthology.org/2021.naacl-main.51/)**Emiel van Miltenburg, Chris van der Lee, Emiel Krahmer · 🏆 Best Thematic Paper*20 citations*
8. **[Query2Prod2Vec: Grounded Word Embeddings for eCommerce](https://aclanthology.org/2021.naacl-industry.20/)**Federico Bianchi, Jacopo Tagliabue, Bingqing Yu · Industry Papers · 🏆 Best Industry Paper*10 citations*

## Most cited papers

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

1. **[mT5: A Massively Multilingual Pre-trained Text-to-Text Transformer](https://md.research.elamur.ai/free/en/papers/xue-2021-mt5-massively-multilingual-pre-trained/)**Linting Xue, Noah Constant, Adam Roberts et al.*1,621 citations · our summary*
2. **[It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners](https://md.research.elamur.ai/free/en/papers/schick-2021-it-s-not-just-size/)**Timo Schick, Hinrich Schütze · 🏆 Outstanding Long Paper*685 citations · our summary*
3. **[Unified Pre-training for Program Understanding and Generation](https://md.research.elamur.ai/free/en/papers/ahmad-2021-unified-pre-training-program-understanding/)**Wasi Ahmad, Saikat Chakraborty, Baishakhi Ray et al.*608 citations · our summary*
4. **[QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering](https://aclanthology.org/2021.naacl-main.45/)**Michihiro Yasunaga, Hongyu Ren, Antoine Bosselut et al.*522 citations*
5. **[A Frustratingly Easy Approach for Entity and Relation Extraction](https://md.research.elamur.ai/free/en/papers/zhong-2020-frustratingly-easy-approach-entity-relation/)**Zexuan Zhong, Danqi Chen*477 citations · our summary*
6. **[RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/qu-2021-rocketqa-optimized-training-approach-dense/)**Yingqi Qu, Yuchen Ding, Jing Liu et al.*356 citations · our summary*
7. **[KILT: a Benchmark for Knowledge Intensive Language Tasks](https://md.research.elamur.ai/free/en/papers/petroni-2020-kilt-benchmark-knowledge-intensive-language/)**Fabio Petroni, Aleksandra Piktus, Angela Fan et al.*339 citations · our summary*
8. **[Self-Alignment Pretraining for Biomedical Entity Representations](https://md.research.elamur.ai/free/en/papers/liu-2021-self-alignment-pretraining-biomedical-entity/)**Fangyu Liu, Ehsan Shareghi, Zaiqiao Meng et al.*335 citations · our summary*
9. **[Learning How to Ask: Querying LMs with Mixtures of Soft Prompts](https://md.research.elamur.ai/free/en/papers/qin-2021-learning-ask-querying-lms-mixtures/)**Guanghui Qin, Jason Eisner · 🏆 Best Short Paper*328 citations · our summary*
10. **[Are NLP Models really able to Solve Simple Math Word Problems?](https://md.research.elamur.ai/free/en/papers/patel-2021-are-nlp-models-really-able/)**Arkil Patel, Satwik Bhattamishra, Navin Goyal*290 citations · our summary*

## All accepted papers (560)

The most cited first; 74 with our summary link to their page here, the others to the original.

1. **[mT5: A Massively Multilingual Pre-trained Text-to-Text Transformer](https://md.research.elamur.ai/free/en/papers/xue-2021-mt5-massively-multilingual-pre-trained/)**Linting Xue, Noah Constant, Adam Roberts et al.*1,621 citations · our summary*
2. **[It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners](https://md.research.elamur.ai/free/en/papers/schick-2021-it-s-not-just-size/)**Timo Schick, Hinrich Schütze · 🏆 Outstanding Long Paper*685 citations · our summary*
3. **[Unified Pre-training for Program Understanding and Generation](https://md.research.elamur.ai/free/en/papers/ahmad-2021-unified-pre-training-program-understanding/)**Wasi Ahmad, Saikat Chakraborty, Baishakhi Ray et al.*608 citations · our summary*
4. **[QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering](https://aclanthology.org/2021.naacl-main.45/)**Michihiro Yasunaga, Hongyu Ren, Antoine Bosselut et al.*522 citations*
5. **[A Frustratingly Easy Approach for Entity and Relation Extraction](https://md.research.elamur.ai/free/en/papers/zhong-2020-frustratingly-easy-approach-entity-relation/)**Zexuan Zhong, Danqi Chen*477 citations · our summary*
6. **[RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/qu-2021-rocketqa-optimized-training-approach-dense/)**Yingqi Qu, Yuchen Ding, Jing Liu et al.*356 citations · our summary*
7. **[KILT: a Benchmark for Knowledge Intensive Language Tasks](https://md.research.elamur.ai/free/en/papers/petroni-2020-kilt-benchmark-knowledge-intensive-language/)**Fabio Petroni, Aleksandra Piktus, Angela Fan et al.*339 citations · our summary*
8. **[Self-Alignment Pretraining for Biomedical Entity Representations](https://md.research.elamur.ai/free/en/papers/liu-2021-self-alignment-pretraining-biomedical-entity/)**Fangyu Liu, Ehsan Shareghi, Zaiqiao Meng et al.*335 citations · our summary*
9. **[Learning How to Ask: Querying LMs with Mixtures of Soft Prompts](https://md.research.elamur.ai/free/en/papers/qin-2021-learning-ask-querying-lms-mixtures/)**Guanghui Qin, Jason Eisner · 🏆 Best Short Paper*328 citations · our summary*
10. **[Are NLP Models really able to Solve Simple Math Word Problems?](https://md.research.elamur.ai/free/en/papers/patel-2021-are-nlp-models-really-able/)**Arkil Patel, Satwik Bhattamishra, Navin Goyal*290 citations · our summary*
11. **[A Survey on Recent Approaches for Natural Language Processing in Low-Resource Scenarios](https://md.research.elamur.ai/free/en/papers/hedderich-2021-survey-recent-approaches-natural-language/)**Michael A. Hedderich, Lukas Lange, Heike Adel et al.*260 citations · our summary*
12. **[Factual Probing Is MASK: Learning vs. Learning to Recall](https://md.research.elamur.ai/free/en/papers/zhong-2021-factual-probing-is-mask-learning/)**Zexuan Zhong, Dan Friedman, Danqi Chen*260 citations · our summary*
13. **[Document-Level Event Argument Extraction by Conditional Generation](https://md.research.elamur.ai/free/en/papers/li-2021-document-level-event-argument-extraction/)**Sha Li, Heng Ji, Jiawei Han*254 citations · our summary*
14. **[InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training](https://aclanthology.org/2021.naacl-main.280/)**Zewen Chi, Li Dong, Furu Wei et al.*249 citations*
15. **[Dynabench: Rethinking Benchmarking in NLP](https://aclanthology.org/2021.naacl-main.324/)**Douwe Kiela, Max Bartolo, Yixin Nie et al.*229 citations*
16. **[GSum: A General Framework for Guided Neural Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/dou-2021-gsum-general-framework-guided-neural/)**Zi-Yi Dou, Pengfei Liu, Hiroaki Hayashi et al.*200 citations · our summary*
17. **[Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics](https://md.research.elamur.ai/free/en/papers/pagnoni-2021-understanding-factuality-abstractive-summarization-frank/)**Artidoro Pagnoni, Vidhisha Balachandran, Yulia Tsvetkov*190 citations · our summary*
18. **[Aspect-based Sentiment Analysis with Type-aware Graph Convolutional Networks and Layer Ensemble](https://aclanthology.org/2021.naacl-main.231/)**Yuanhe Tian, Guimin Chen, Yan Song*187 citations*
19. **[COIL: Revisit Exact Lexical Match in Information Retrieval with Contextualized Inverted List](https://md.research.elamur.ai/free/en/papers/gao-2021-coil-revisit-exact-lexical-match/)**Luyu Gao, Zhuyun Dai, Jamie Callan*186 citations · our summary*
20. **[Supporting Clustering with Contrastive Learning](https://md.research.elamur.ai/free/en/papers/zhang-2021-supporting-clustering-contrastive-learning/)**Dejiao Zhang, Feng Nan, Xiaokai Wei et al.*185 citations · our summary*
21. **[How many data points is a prompt worth?](https://md.research.elamur.ai/free/en/papers/scao-2021-how-many-data-points-is/)**Teven Le Scao, Alexander Rush · 🏆 Outstanding Short Paper*179 citations · our summary*
22. **[Contextualized Perturbation for Textual Adversarial Attack](https://md.research.elamur.ai/free/en/papers/li-2021-contextualized-perturbation-textual-adversarial-attack/)**Dianqi Li, Yizhe Zhang, Hao Peng et al.*178 citations · our summary*
23. **[Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks](https://md.research.elamur.ai/free/en/papers/thakur-2021-augmented-sbert-data-augmentation-method/)**Nandan Thakur, Nils Reimers, Johannes Daxenberger et al.*176 citations · our summary*
24. **[QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization](https://md.research.elamur.ai/free/en/papers/zhong-2021-qmsum-new-benchmark-query-based/)**Ming Zhong, Da Yin, Tao Yu et al.*174 citations · our summary*
25. **[Does syntax matter? A strong baseline for Aspect-based Sentiment Analysis with RoBERTa](https://aclanthology.org/2021.naacl-main.146/)**Junqi Dai, Hang Yan, Tianxiang Sun et al.*163 citations*

[See all 560 papers in NAACL 2021 — accepted papers →](https://md.research.elamur.ai/free/en/venues/naacl/2021/papers/)

## Papers with our summary in our library (74)

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

1. **[mT5: A Massively Multilingual Pre-trained Text-to-Text Transformer](https://md.research.elamur.ai/free/en/papers/xue-2021-mt5-massively-multilingual-pre-trained/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Linting Xue, Noah Constant, Adam Roberts, et al.*2021 · 3,197 citations*
2. **[It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners](https://md.research.elamur.ai/free/en/papers/schick-2021-it-s-not-just-size/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Timo Schick, Hinrich Schütze*2021 · 1,122 citations*
3. [**Are NLP Models really able to Solve Simple Math Word Problems?**Arkil Patel, Satwik Bhattamishra, Navin Goyal*2021 · 883 citations*](https://md.research.elamur.ai/free/en/papers/patel-2021-are-nlp-models-really-able/)
4. **[Unified Pre-training for Program Understanding and Generation](https://md.research.elamur.ai/free/en/papers/ahmad-2021-unified-pre-training-program-understanding/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Wasi Ahmad, Saikat Chakraborty, Baishakhi Ray, et al.*2021 · 748 citations*
5. **[Learning To Retrieve Prompts for In-Context Learning](https://md.research.elamur.ai/free/en/papers/rubin-2021-learning-retrieve-prompts-context-learning/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ohad Rubin, Jonathan Herzig, Jonathan Berant*2021 · 717 citations*
6. **[RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/qu-2021-rocketqa-optimized-training-approach-dense/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yingqi Qu, Yuchen Ding, Jing Liu, et al.*2021 · 602 citations*
7. **[Learning How to Ask: Querying LMs with Mixtures of Soft Prompts](https://md.research.elamur.ai/free/en/papers/qin-2021-learning-ask-querying-lms-mixtures/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Guanghui Qin, Jason Eisner*2021 · 568 citations*
8. **[Self-Alignment Pretraining for Biomedical Entity Representations](https://md.research.elamur.ai/free/en/papers/liu-2021-self-alignment-pretraining-biomedical-entity/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Fangyu Liu, Ehsan Shareghi, Zaiqiao Meng, et al.*2021 · 434 citations*
9. **[Document-Level Event Argument Extraction by Conditional Generation](https://md.research.elamur.ai/free/en/papers/li-2021-document-level-event-argument-extraction/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Sha Li, Heng Ji, Jiawei Han*2021 · 432 citations*
10. **[Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics](https://md.research.elamur.ai/free/en/papers/pagnoni-2021-understanding-factuality-abstractive-summarization-frank/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Artidoro Pagnoni, Vidhisha Balachandran, Yulia Tsvetkov*2021 · 418 citations*
11. **[Factual Probing Is MASK: Learning vs. Learning to Recall](https://md.research.elamur.ai/free/en/papers/zhong-2021-factual-probing-is-mask-learning/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Zexuan Zhong, Dan Friedman, Danqi Chen*2021 · 411 citations*
12. **[A Survey on Recent Approaches for Natural Language Processing in Low-Resource Scenarios](https://md.research.elamur.ai/free/en/papers/hedderich-2021-survey-recent-approaches-natural-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Michael A. Hedderich, Lukas Lange, Heike Adel, et al.*2021 · 400 citations*
13. **[QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization](https://md.research.elamur.ai/free/en/papers/zhong-2021-qmsum-new-benchmark-query-based/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ming Zhong, Da Yin, Tao Yu, et al.*2021 · 400 citations*
14. **[A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers](https://md.research.elamur.ai/free/en/papers/dasigi-2021-dataset-information-seeking-questions-answers/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Pradeep Dasigi, Kyle Lo, Iz Beltagy, et al.*2021 · 374 citations*
15. **[Efficient Attentions for Long Document Summarization](https://md.research.elamur.ai/free/en/papers/huang-2021-efficient-attentions-long-document-summarization/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Luyang Huang, Shuyang Cao, Nikolaus Parulian, et al.*2021 · 335 citations*
16. **[GSum: A General Framework for Guided Neural Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/dou-2021-gsum-general-framework-guided-neural/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Zi-Yi Dou, Pengfei Liu, Hiroaki Hayashi, et al.*2021 · 319 citations*
17. **[How many data points is a prompt worth?](https://md.research.elamur.ai/free/en/papers/scao-2021-how-many-data-points-is/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Teven Le Scao, Alexander Rush*2021 · 316 citations*
18. **[Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence](https://md.research.elamur.ai/free/en/papers/schuster-2021-get-your-vitamin-c-robust/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Tal Schuster, Adam Fisch, Regina Barzilay*2021 · 289 citations*
19. **[Contextualized Perturbation for Textual Adversarial Attack](https://md.research.elamur.ai/free/en/papers/li-2021-contextualized-perturbation-textual-adversarial-attack/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Dianqi Li, Yizhe Zhang, Hao Peng, et al.*2021 · 282 citations*
20. **[Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks](https://md.research.elamur.ai/free/en/papers/thakur-2021-augmented-sbert-data-augmentation-method/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Nandan Thakur, Nils Reimers, Johannes Daxenberger, et al.*2021 · 276 citations*
21. **[COIL: Revisit Exact Lexical Match in Information Retrieval with Contextualized Inverted List](https://md.research.elamur.ai/free/en/papers/gao-2021-coil-revisit-exact-lexical-match/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Luyu Gao, Zhuyun Dai, Jamie Callan*2021 · 250 citations*
22. **[The Curious Case of Hallucinations in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/raunak-2021-curious-case-hallucinations-neural-machine/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Vikas Raunak, Arul Menezes, Marcin Junczys-Dowmunt*2021 · 241 citations*
23. **[Supporting Clustering with Contrastive Learning](https://md.research.elamur.ai/free/en/papers/zhang-2021-supporting-clustering-contrastive-learning/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Dejiao Zhang, Feng Nan, Xiaokai Wei, et al.*2021 · 239 citations*
24. **[Knowledge Graph Based Synthetic Corpus Generation for Knowledge-Enhanced Language Model Pre-training](https://md.research.elamur.ai/free/en/papers/agarwal-2021-knowledge-graph-based-synthetic-corpus/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Oshin Agarwal, Heming Ge, Siamak Shakeri, et al.*2021 · 238 citations*
25. **[FUDGE: Controlled Text Generation With Future Discriminators](https://md.research.elamur.ai/free/en/papers/yang-2021-fudge-controlled-text-generation-future/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kevin Yang, Dan Klein*2021 · 235 citations*

[See all 74 works in NAACL 2021 — accepted papers →](https://md.research.elamur.ai/free/en/venues/naacl/2021/works/)

## Top topics

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

[Language models & pretraining (12)](https://md.research.elamur.ai/free/en/topics/language-models/) · [Summarization (9)](https://md.research.elamur.ai/free/en/topics/summarization/) · [Coreference resolution (7)](https://md.research.elamur.ai/free/en/topics/coreference-resolution/) · [Question answering (6)](https://md.research.elamur.ai/free/en/topics/question-answering/) · [Sentiment & emotion (5)](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · [Information retrieval & search (5)](https://md.research.elamur.ai/free/en/topics/information-retrieval/) · [Discourse analysis (4)](https://md.research.elamur.ai/free/en/topics/discourse-analysis/) · [Dialogue systems (4)](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [Multilingual & cross-lingual NLP (4)](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/) · [Text generation (3)](https://md.research.elamur.ai/free/en/topics/text-generation/) · [Evaluation & benchmarks (3)](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Reasoning (3)](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Machine translation (2)](https://md.research.elamur.ai/free/en/topics/machine-translation/) · [Code & programming languages (2)](https://md.research.elamur.ai/free/en/topics/code-and-programming/) · [Interpretability (2)](https://md.research.elamur.ai/free/en/topics/interpretability/)

**10 more topics**

[Speech act theory (1)](https://md.research.elamur.ai/free/en/topics/speech-act-theory/) · [Implicature (1)](https://md.research.elamur.ai/free/en/topics/implicature/) · [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/) · [Knowledge graphs & ontologies (1)](https://md.research.elamur.ai/free/en/topics/knowledge-graphs/) · [Legal AI (1)](https://md.research.elamur.ai/free/en/topics/legal-ai/) · [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/) · [Vision & language (1)](https://md.research.elamur.ai/free/en/topics/multimodal/) · [English (1)](https://md.research.elamur.ai/free/en/topics/english/)

## Fields

[Computer Science (74)](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities (73)](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Social Sciences (5)](https://md.research.elamur.ai/free/en/shelves/social-sciences/) · [Biochemistry, Genetics and Molecular Biology (1)](https://md.research.elamur.ai/free/en/shelves/biochemistry-genetics-and-molecular-biology/) · [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.

[🧑‍🔬**Heng Ji**3 works here · 815 citations](https://md.research.elamur.ai/free/en/authors/heng-ji/) · [🧑‍🔬**Dirk Hovy**3 works here · 567 citations](https://md.research.elamur.ai/free/en/authors/dirk-hovy/) · [🧑‍🔬**Rami Al-Rfou**2 works here · 3,435 citations](https://md.research.elamur.ai/free/en/authors/rami-al-rfou/) · [🧑‍🔬**Jonathan Herzig**2 works here · 850 citations](https://md.research.elamur.ai/free/en/authors/jonathan-herzig/) · [🧑‍🔬**Yang Liu**2 works here · 580 citations](https://md.research.elamur.ai/free/en/authors/yang-liu/) · [🧑‍🔬**Ahmed Awadallah**2 works here · 566 citations](https://md.research.elamur.ai/free/en/authors/ahmed-awadallah/) · [🧑‍🔬**Mohit Iyyer**2 works here · 415 citations](https://md.research.elamur.ai/free/en/authors/mohit-iyyer/) · [🧑‍🔬**Iryna Gurevych**2 works here · 379 citations](https://md.research.elamur.ai/free/en/authors/iryna-gurevych/) · [🧑‍🔬**Johannes Daxenberger**2 works here · 379 citations](https://md.research.elamur.ai/free/en/authors/johannes-daxenberger/) · [🧑‍🔬**Dan Klein**2 works here · 370 citations](https://md.research.elamur.ai/free/en/authors/dan-klein/) · [🧑‍🔬**Diyi Yang**2 works here · 369 citations](https://md.research.elamur.ai/free/en/authors/diyi-yang/) · [🧑‍🔬**Chenguang Zhu**2 works here · 368 citations](https://md.research.elamur.ai/free/en/authors/chenguang-zhu/)

## Top institutions

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

[🏢**Microsoft** Redmond · United States 6 works here](https://md.research.elamur.ai/free/en/companies/microsoft/) · [🏢**Google** Mountain View · United States 6 works here](https://md.research.elamur.ai/free/en/companies/google/) · [🎓**University of Washington** Seattle · United States 6 works here](https://md.research.elamur.ai/free/en/universities/university-of-washington/) · [🎓**Georgia Institute of Technology** Atlanta · United States 3 works here](https://md.research.elamur.ai/free/en/universities/georgia-institute-of-technology/) · [🎓**University of Illinois Urbana-Champaign** Urbana · United States 3 works here](https://md.research.elamur.ai/free/en/universities/university-of-illinois-urbana-champaign/) · [🎓**Technische Universität Darmstadt** Darmstadt · Germany 3 works here](https://md.research.elamur.ai/free/en/universities/technische-universitat-darmstadt/) · [🔬**Allen Institute for Artificial Intelligence** Seattle · United States 3 works here](https://md.research.elamur.ai/free/en/labs/allen-institute-for-artificial-intelligence/) · [🎓**Bocconi University** Milan · Italy 3 works here](https://md.research.elamur.ai/free/en/universities/bocconi-university/) · [🎓**Carnegie Mellon University** Pittsburgh · United States 3 works here](https://md.research.elamur.ai/free/en/universities/carnegie-mellon-university/) · [🎓**Columbia University** New York · United States 3 works here](https://md.research.elamur.ai/free/en/universities/columbia-university/) · [🎓**The University of Texas at Austin** Austin · United States 3 works here](https://md.research.elamur.ai/free/en/universities/the-university-of-texas-at-austin/) · [🏢**Adobe Systems** San Jose · United States 2 works here](https://md.research.elamur.ai/free/en/companies/adobe-systems/)

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

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