---
title: "EMNLP 2023 — accepted papers — Elamur Research"
description: "EMNLP 2023 — accepted papers: 80 papers in the Elamur Research library (Singapore, Singapore), with our summaries, ranked by citations."
canonical: "https://research.elamur.ai/free/en/venues/emnlp/2023/"
---
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# EMNLP 2023 — accepted papers

EMNLP 2023 is the 2023 edition of the Conference on Empirical Methods in Natural Language Processing (EMNLP), held in Singapore, Singapore, 6–10 December 2023 (publisher: Association for Computational Linguistics). The ACL Anthology lists 1,182 papers of it in 4 tracks; our library holds 80 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

[**1,182** papers in the proceedings](#all) · [**80** works in our library](https://md.research.elamur.ai/free/en/venues/emnlp/2023/works/) · [**15,928** citations of these works](https://md.research.elamur.ai/free/en/venues/emnlp/2023/works/)**Singapore, Singapore** where it was held**6–10 December 2023** when

## Tracks

Main 1,047Industry Track 77System Demonstrations 52Tutorial Abstracts 6

## Most cited papers

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

1. **[G-Eval: NLG Evaluation using Gpt-4 with Better Human Alignment](https://aclanthology.org/2023.emnlp-main.153/)**Yang Liu, Dan Iter, Yichong Xu et al.*904 citations*
2. **[Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding](https://aclanthology.org/2023.emnlp-demo.49/)**Hang Zhang, Xin Li, Lidong Bing · System Demonstrations*586 citations*
3. **[Evaluating Object Hallucination in Large Vision-Language Models](https://md.research.elamur.ai/free/en/papers/li-2023-evaluating-object-hallucination-large-vision/)**Yifan Li, Yifan Du, Kun Zhou et al.*559 citations · our summary*
4. **[SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models](https://aclanthology.org/2023.emnlp-main.557/)**Potsawee Manakul, Adian Liusie, Mark Gales*512 citations*
5. **[Is ChatGPT a General-Purpose Natural Language Processing Task Solver?](https://md.research.elamur.ai/free/en/papers/qin-2023-chatgpt-general-purpose-natural-language/)**Chengwei Qin, Aston Zhang, Zhuosheng Zhang et al.*504 citations · our summary*
6. **[Active Retrieval Augmented Generation](https://aclanthology.org/2023.emnlp-main.495/)**Zhengbao Jiang, Frank Xu, Luyu Gao et al.*462 citations*
7. **[CodeT5+: Open Code Large Language Models for Code Understanding and Generation](https://aclanthology.org/2023.emnlp-main.68/)**Yue Wang, Hung Le, Akhilesh Gotmare et al.*433 citations*
8. **[GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints](https://md.research.elamur.ai/free/en/papers/ainslie-2023-gqa-training-generalized-multi-query/)**Joshua Ainslie, James Lee-Thorp, Michiel de Jong et al.*428 citations · our summary*
9. **[FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation](https://md.research.elamur.ai/free/en/papers/min-2023-factscore-fine-grained-atomic-evaluation/)**Sewon Min, Kalpesh Krishna, Xinxi Lyu et al.*374 citations · our summary*
10. **[HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2023-halueval-large-scale-hallucination-evaluation/)**Junyi Li, Xiaoxue Cheng, Xin Zhao et al.*321 citations · our summary*

## All accepted papers (1,182)

The most cited first; 80 with our summary link to their page here, the others to the original.

1. **[G-Eval: NLG Evaluation using Gpt-4 with Better Human Alignment](https://aclanthology.org/2023.emnlp-main.153/)**Yang Liu, Dan Iter, Yichong Xu et al.*904 citations*
2. **[Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding](https://aclanthology.org/2023.emnlp-demo.49/)**Hang Zhang, Xin Li, Lidong Bing · System Demonstrations*586 citations*
3. **[Evaluating Object Hallucination in Large Vision-Language Models](https://md.research.elamur.ai/free/en/papers/li-2023-evaluating-object-hallucination-large-vision/)**Yifan Li, Yifan Du, Kun Zhou et al.*559 citations · our summary*
4. **[SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models](https://aclanthology.org/2023.emnlp-main.557/)**Potsawee Manakul, Adian Liusie, Mark Gales*512 citations*
5. **[Is ChatGPT a General-Purpose Natural Language Processing Task Solver?](https://md.research.elamur.ai/free/en/papers/qin-2023-chatgpt-general-purpose-natural-language/)**Chengwei Qin, Aston Zhang, Zhuosheng Zhang et al.*504 citations · our summary*
6. **[Active Retrieval Augmented Generation](https://aclanthology.org/2023.emnlp-main.495/)**Zhengbao Jiang, Frank Xu, Luyu Gao et al.*462 citations*
7. **[CodeT5+: Open Code Large Language Models for Code Understanding and Generation](https://aclanthology.org/2023.emnlp-main.68/)**Yue Wang, Hung Le, Akhilesh Gotmare et al.*433 citations*
8. **[GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints](https://md.research.elamur.ai/free/en/papers/ainslie-2023-gqa-training-generalized-multi-query/)**Joshua Ainslie, James Lee-Thorp, Michiel de Jong et al.*428 citations · our summary*
9. **[FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation](https://md.research.elamur.ai/free/en/papers/min-2023-factscore-fine-grained-atomic-evaluation/)**Sewon Min, Kalpesh Krishna, Xinxi Lyu et al.*374 citations · our summary*
10. **[HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2023-halueval-large-scale-hallucination-evaluation/)**Junyi Li, Xiaoxue Cheng, Xin Zhao et al.*321 citations · our summary*
11. **[Query Rewriting in Retrieval-Augmented Large Language Models](https://md.research.elamur.ai/free/en/papers/ma-2023-query-rewriting-retrieval-augmented-large/)**Xinbei Ma, Yeyun Gong, Pengcheng He et al.*263 citations · our summary*
12. **[Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agents](https://md.research.elamur.ai/free/en/papers/sun-2023-chatgpt-good-search-investigating-large/)**Weiwei Sun, Lingyong Yan, Xinyu Ma et al.*262 citations · our summary*
13. **[LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models](https://md.research.elamur.ai/free/en/papers/hu-2023-llm-adapters-adapter-family-parameter/)**Zhiqiang Hu, Lei Wang, Yihuai Lan et al.*238 citations · our summary*
14. **[StructGPT: A General Framework for Large Language Model to Reason over Structured Data](https://aclanthology.org/2023.emnlp-main.574/)**Jinhao Jiang, Kun Zhou, Zican Dong et al.*234 citations*
15. **[Large Language Models Can Self-Improve](https://md.research.elamur.ai/free/en/papers/huang-2023-large-language-models-can-self/)**Jiaxin Huang, Shixiang Gu, Le Hou et al.*219 citations · our summary*
16. **[Enabling Large Language Models to Generate Text with Citations](https://md.research.elamur.ai/free/en/papers/gao-2023-enabling-large-language-models-generate/)**Tianyu Gao, Howard Yen, Jiatong Yu et al.*204 citations · our summary*
17. **[Query2doc: Query Expansion with Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2023-query2doc-query-expansion-large-language/)**Liang Wang, Nan Yang, Furu Wei*200 citations · our summary*
18. **[Learning Language-guided Adaptive Hyper-modality Representation for Multimodal Sentiment Analysis](https://aclanthology.org/2023.emnlp-main.49/)**Haoyu Zhang, Yu Wang, Guanghao Yin et al.*188 citations*
19. **[Automatic Prompt Optimization with “Gradient Descent” and Beam Search](https://md.research.elamur.ai/free/en/papers/pryzant-2023-automatic-prompt-optimization-gradient-descent/)**Reid Pryzant, Dan Iter, Jerry Li et al.*187 citations · our summary*
20. **[RepoCoder: Repository-Level Code Completion Through Iterative Retrieval and Generation](https://aclanthology.org/2023.emnlp-main.151/)**Fengji Zhang, Bei Chen, Yue Zhang et al.*164 citations*
21. **[GPT-RE: In-context Learning for Relation Extraction using Large Language Models](https://md.research.elamur.ai/free/en/papers/wan-2023-gpt-re-context-learning-relation/)**Zhen Wan, Fei Cheng, Zhuoyuan Mao et al.*162 citations · our summary*
22. **[Reasoning with Language Model is Planning with World Model](https://aclanthology.org/2023.emnlp-main.507/)**Shibo Hao, Yi Gu, Haodi Ma et al.*158 citations*
23. **[LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2023-llmlingua-compressing-prompts-accelerated-inference/)**Huiqiang Jiang, Qianhui Wu, Chin-Yew Lin et al.*154 citations · our summary*
24. **[Towards Interpretable Mental Health Analysis with Large Language Models](https://aclanthology.org/2023.emnlp-main.370/)**Kailai Yang, Shaoxiong Ji, Tianlin Zhang et al.*153 citations*
25. **[Document-Level Machine Translation with Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2023-document-level-machine-translation-large/)**Longyue Wang, Chenyang Lyu, Tianbo Ji et al.*150 citations · our summary*

[See all 1,182 papers in EMNLP 2023 — accepted papers →](https://md.research.elamur.ai/free/en/venues/emnlp/2023/papers/)

## Papers with our summary in our library (80)

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

1. **[GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints](https://md.research.elamur.ai/free/en/papers/ainslie-2023-gqa-training-generalized-multi-query/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Joshua Ainslie, James Lee-Thorp, Michiel de Jong, et al.*2023 · 1,012 citations*
2. **[Evaluating Object Hallucination in Large Vision-Language Models](https://md.research.elamur.ai/free/en/papers/li-2023-evaluating-object-hallucination-large-vision/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yifan Li, Yifan Du, Kun Zhou, et al.*2023 · 986 citations*
3. **[FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation](https://md.research.elamur.ai/free/en/papers/min-2023-factscore-fine-grained-atomic-evaluation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sewon Min, Kalpesh Krishna, Xinxi Lyu, et al.*2023 · 971 citations*
4. **[Is ChatGPT a General-Purpose Natural Language Processing Task Solver?](https://md.research.elamur.ai/free/en/papers/qin-2023-chatgpt-general-purpose-natural-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chengwei Qin, Aston Zhang, Zhuosheng Zhang, et al.*2023 · 823 citations*
5. **[HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2023-halueval-large-scale-hallucination-evaluation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Junyi Li, Xiaoxue Cheng, Wayne Xin Zhao, et al.*2023 · 647 citations*
6. **[Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate](https://md.research.elamur.ai/free/en/papers/liang-2023-encouraging-divergent-thinking-large-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tian Liang, Zhiwei He, Wenxiang Jiao, et al.*2023 · 643 citations*
7. **[Video-LLaVA: Learning United Visual Representation by Alignment Before Projection](https://md.research.elamur.ai/free/en/papers/lin-2023-video-llava-learning-united-visual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bin Lin, Yang Ye, Bin Zhu, et al.*2023 · 614 citations*
8. **[Large Language Models Can Self-Improve](https://md.research.elamur.ai/free/en/papers/huang-2023-large-language-models-can-self/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiaxin Huang, Shixiang Gu, Le Hou, et al.*2023 · 563 citations*
9. **[Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agents](https://md.research.elamur.ai/free/en/papers/sun-2023-chatgpt-good-search-investigating-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Weiwei Sun, Lingyong Yan, Xinyu Ma, et al.*2023 · 494 citations*
10. **[Enabling Large Language Models to Generate Text with Citations](https://md.research.elamur.ai/free/en/papers/gao-2023-enabling-large-language-models-generate/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tianyu Gao, Howard Yen, Jiatong Yu, et al.*2023 · 477 citations*
11. **[LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models](https://md.research.elamur.ai/free/en/papers/hu-2023-llm-adapters-adapter-family-parameter/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhiqiang Hu, Lei Wang, Yihuai Lan, et al.*2023 · 399 citations*
12. **[Automatic Prompt Optimization with “Gradient Descent” and Beam Search](https://md.research.elamur.ai/free/en/papers/pryzant-2023-automatic-prompt-optimization-gradient-descent/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Reid Pryzant, Dan Iter, Jerry Li, et al.*2023 · 397 citations*
13. **[Query Rewriting in Retrieval-Augmented Large Language Models](https://md.research.elamur.ai/free/en/papers/ma-2023-query-rewriting-retrieval-augmented-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xinbei Ma, Yeyun Gong, Pengcheng He, et al.*2023 · 383 citations*
14. **[Query2doc: Query Expansion with Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2023-query2doc-query-expansion-large-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Liang Wang, Nan Yang, Furu Wei*2023 · 353 citations*
15. **[LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2023-llmlingua-compressing-prompts-accelerated-inference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Huiqiang Jiang, Qianhui Wu, Chin-Yew Lin, et al.*2023 · 335 citations*
16. **[Character-LLM: A Trainable Agent for Role-Playing](https://md.research.elamur.ai/free/en/papers/shao-2023-character-llm-trainable-agent-role/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yunfan Shao, Linyang Li, Junqi Dai, et al.*2023 · 300 citations*
17. **[Document-Level Machine Translation with Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2023-document-level-machine-translation-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Longyue Wang, Chenyang Lyu, Tianbo Ji, et al.*2023 · 296 citations*
18. **[Baize: An Open-Source Chat Model with Parameter-Efficient Tuning on Self-Chat Data](https://md.research.elamur.ai/free/en/papers/xu-2023-baize-open-source-chat-model/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Canwen Xu, Daya Guo, Nan Duan, et al.*2023 · 296 citations*
19. **[API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMs](https://md.research.elamur.ai/free/en/papers/li-2023-api-bank-comprehensive-benchmark-tool/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Minghao Li, Yingxiu Zhao, Bowen Yu, et al.*2023 · 282 citations*
20. **[GPT-RE: In-context Learning for Relation Extraction using Large Language Models](https://md.research.elamur.ai/free/en/papers/wan-2023-gpt-re-context-learning-relation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Wan, Fei Cheng, Zhuoyuan Mao, et al.*2023 · 253 citations*
21. **[Synthetic Data Generation with Large Language Models for Text Classification: Potential and Limitations](https://md.research.elamur.ai/free/en/papers/li-2023-synthetic-data-generation-large-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhuoyan Li, Hangxiao Zhu, Zhuoran Lu, et al.*2023 · 242 citations*
22. **[Compressing Context to Enhance Inference Efficiency of Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2023-compressing-context-enhance-inference-efficiency/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yucheng Li, Bo Dong, Frank Guerin, et al.*2023 · 209 citations*
23. **[SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization](https://md.research.elamur.ai/free/en/papers/kim-2023-soda-million-scale-dialogue-distillation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hyunwoo Kim, Jack Hessel, Liwei Jiang, et al.*2023 · 201 citations*
24. **[Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human Feedback](https://md.research.elamur.ai/free/en/papers/lai-2023-okapi-instruction-tuned-large-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Viet Lai, Chien Nguyen, Nghia Ngo, et al.*2023 · 194 citations*
25. **[Adapting Language Models to Compress Contexts](https://md.research.elamur.ai/free/en/papers/chevalier-2023-adapting-language-models-compress-contexts/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Alexis Chevalier, Alexander Wettig, Anirudh Ajith, et al.*2023 · 179 citations*

[See all 80 works in EMNLP 2023 — accepted papers →](https://md.research.elamur.ai/free/en/venues/emnlp/2023/works/)

## Top topics

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

[Language models & pretraining (34)](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning (11)](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Multilingual & cross-lingual NLP (7)](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/) · [English (6)](https://md.research.elamur.ai/free/en/topics/english/) · [Discourse analysis (5)](https://md.research.elamur.ai/free/en/topics/discourse-analysis/) · [Evaluation & benchmarks (5)](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Information retrieval & search (5)](https://md.research.elamur.ai/free/en/topics/information-retrieval/) · [Question answering (4)](https://md.research.elamur.ai/free/en/topics/question-answering/) · [Vision & language (4)](https://md.research.elamur.ai/free/en/topics/multimodal/) · [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/) · [Implicature (2)](https://md.research.elamur.ai/free/en/topics/implicature/) · [Coreference resolution (2)](https://md.research.elamur.ai/free/en/topics/coreference-resolution/) · [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/)

**10 more topics**

[Semitic languages (2)](https://md.research.elamur.ai/free/en/topics/semitic-languages/) · [Efficient models & compression (2)](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Idioms & multiword expressions (2)](https://md.research.elamur.ai/free/en/topics/multiword-expressions/) · [Information extraction (1)](https://md.research.elamur.ai/free/en/topics/information-extraction/) · [Summarization (1)](https://md.research.elamur.ai/free/en/topics/summarization/) · [Morphology (1)](https://md.research.elamur.ai/free/en/topics/morphology/) · [Knowledge graphs & ontologies (1)](https://md.research.elamur.ai/free/en/topics/knowledge-graphs/) · [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/) · [Grammatical error correction & learner language (1)](https://md.research.elamur.ai/free/en/topics/grammatical-error-correction/)

## Fields

[Computer Science (79)](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities (76)](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Social Sciences (6)](https://md.research.elamur.ai/free/en/shelves/social-sciences/) · [Psychology (2)](https://md.research.elamur.ai/free/en/shelves/psychology/) · [Business, Management and Accounting (1)](https://md.research.elamur.ai/free/en/shelves/business-management-and-accounting/) · [Neuroscience (1)](https://md.research.elamur.ai/free/en/shelves/neuroscience/)

## Top authors

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

[🧑‍🔬**Diyi Yang**4 works here · 1,061 citations](https://md.research.elamur.ai/free/en/authors/diyi-yang/) · [🧑‍🔬**Ji-Rong Wen**2 works here · 1,633 citations](https://md.research.elamur.ai/free/en/authors/ji-rong-wen/) · [🧑‍🔬**James Lee-Thorp**2 works here · 1,095 citations](https://md.research.elamur.ai/free/en/authors/james-lee-thorp/) · [🧑‍🔬**Joshua Ainslie**2 works here · 1,095 citations](https://md.research.elamur.ai/free/en/authors/joshua-ainslie/) · [🧑‍🔬**Michiel de Jong**2 works here · 1,095 citations](https://md.research.elamur.ai/free/en/authors/michiel-de-jong/) · [🧑‍🔬**Sumit Sanghai**2 works here · 1,095 citations](https://md.research.elamur.ai/free/en/authors/sumit-sanghai/) · [🧑‍🔬**Yury Zemlyanskiy**2 works here · 1,095 citations](https://md.research.elamur.ai/free/en/authors/yury-zemlyanskiy/) · [🧑‍🔬**Luke Zettlemoyer**2 works here · 1,088 citations](https://md.research.elamur.ai/free/en/authors/luke-zettlemoyer/) · [🧑‍🔬**Jiaao Chen**2 works here · 943 citations](https://md.research.elamur.ai/free/en/authors/jiaao-chen/) · [🧑‍🔬**Shuming Shi**2 works here · 939 citations](https://md.research.elamur.ai/free/en/authors/shuming-shi/) · [🧑‍🔬**Zhaopeng Tu**2 works here · 939 citations](https://md.research.elamur.ai/free/en/authors/zhaopeng-tu/) · [🧑‍🔬**Nan Duan**2 works here · 679 citations](https://md.research.elamur.ai/free/en/authors/nan-duan/)

## Top institutions

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

[🏢**Google** Mountain View · United States 7 works here](https://md.research.elamur.ai/free/en/companies/google/) · [🔬**Allen Institute for Artificial Intelligence** Seattle · United States 7 works here](https://md.research.elamur.ai/free/en/labs/allen-institute-for-artificial-intelligence/) · [🎓**Carnegie Mellon University** Pittsburgh · United States 7 works here](https://md.research.elamur.ai/free/en/universities/carnegie-mellon-university/) · [🎓**Stanford University** Stanford · United States 6 works here](https://md.research.elamur.ai/free/en/universities/stanford-university/) · [🎓**University of Washington** Seattle · United States 5 works here](https://md.research.elamur.ai/free/en/universities/university-of-washington/) · [🎓**University of Southern California** Los Angeles · United States 4 works here](https://md.research.elamur.ai/free/en/universities/university-of-southern-california/) · [🎓**Georgia Institute of Technology** Atlanta · United States 4 works here](https://md.research.elamur.ai/free/en/universities/georgia-institute-of-technology/) · [🎓**Mohamed bin Zayed University of Artificial Intelligence** Abu Dhabi · United Arab Emirates 4 works here](https://md.research.elamur.ai/free/en/universities/mohamed-bin-zayed-university-of-artificial-intelligence/) · [🏢**Microsoft** Redmond · United States 3 works here](https://md.research.elamur.ai/free/en/companies/microsoft/) · [🎓**Shanghai Jiao Tong University** Shanghai · China 3 works here](https://md.research.elamur.ai/free/en/universities/shanghai-jiao-tong-university/) · [🎓**Princeton University** Princeton · United States 3 works here](https://md.research.elamur.ai/free/en/universities/princeton-university/) · [🎓**Peking University** Beijing · China 3 works here](https://md.research.elamur.ai/free/en/universities/peking-university/)

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

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