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title: "Findings of the Association for Computational Linguistics"
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# Findings of the Association for Computational Linguistics 2023 — accepted papers

Findings of the Association for Computational Linguistics 2023 is the 2023 edition of the Findings of the Association for Computational Linguistics, held in Singapore, December 2023 (publisher: Association for Computational Linguistics). The ACL Anthology lists 2,194 papers of it in 2 tracks; our library holds 95 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

[**2,194** papers in the proceedings](#all) · [**95** works in our library](https://md.research.elamur.ai/free/en/venues/findings/2023/works/) · [**13,645** citations of these works](https://md.research.elamur.ai/free/en/venues/findings/2023/works/)**Singapore** where it was held**December 2023** when

## Tracks

Main 2,157IJCNLP-AACL 2023 (Findings 37

## Most cited papers

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

1. **[Towards Reasoning in Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/huang-2023-reasoning-large-language-models-survey/)**Jie Huang, Kevin Chen-Chuan Chang*409 citations · our summary*
2. **[RWKV: Reinventing RNNs for the Transformer Era](https://aclanthology.org/2023.findings-emnlp.936/)**Bo Peng, Eric Alcaide, Quentin Anthony et al.*367 citations*
3. **[Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes](https://md.research.elamur.ai/free/en/papers/hsieh-2023-distilling-step-step-outperforming-larger/)**Cheng-Yu Hsieh, Chun-Liang Li, Chih-kuan Yeh et al.*307 citations · our summary*
4. **[Measuring and Narrowing the Compositionality Gap in Language Models](https://aclanthology.org/2023.findings-emnlp.378/)**Ofir Press, Muru Zhang, Sewon Min et al.*277 citations*
5. **[Towards Mitigating LLM Hallucination via Self Reflection](https://md.research.elamur.ai/free/en/papers/ji-2023-mitigating-llm-hallucination-self-reflection/)**Ziwei Ji, Tiezheng Yu, Yan Xu et al.*253 citations · our summary*
6. **[Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them](https://md.research.elamur.ai/free/en/papers/suzgun-2023-challenging-big-bench-tasks-whether/)**Mirac Suzgun, Nathan Scales, Nathanael Schärli et al.*243 citations · our summary*
7. **[ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learning](https://md.research.elamur.ai/free/en/papers/lai-2023-chatgpt-beyond-english-comprehensive-evaluation/)**Viet Dac Lai, Nghia Ngo, Amir Pouran Ben Veyseh et al.*228 citations · our summary*
8. **[HuatuoGPT, Towards Taming Language Model to Be a Doctor](https://md.research.elamur.ai/free/en/papers/zhang-2023-huatuogpt-taming-language-model-be/)**Hongbo Zhang, Junying Chen, Feng Jiang et al.*206 citations · our summary*
9. **[Text Classification via Large Language Models](https://md.research.elamur.ai/free/en/papers/sun-2023-text-classification-large-language-models/)**Xiaofei Sun, Xiaoya Li, Jiwei Li et al.*199 citations · our summary*
10. **[Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergy](https://md.research.elamur.ai/free/en/papers/shao-2023-enhancing-retrieval-augmented-large-language/)**Zhihong Shao, Yeyun Gong, Yelong Shen et al.*192 citations · our summary*

## All accepted papers (2,194)

The most cited first; 95 with our summary link to their page here, the others to the original.

1. **[Towards Reasoning in Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/huang-2023-reasoning-large-language-models-survey/)**Jie Huang, Kevin Chen-Chuan Chang*409 citations · our summary*
2. **[RWKV: Reinventing RNNs for the Transformer Era](https://aclanthology.org/2023.findings-emnlp.936/)**Bo Peng, Eric Alcaide, Quentin Anthony et al.*367 citations*
3. **[Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes](https://md.research.elamur.ai/free/en/papers/hsieh-2023-distilling-step-step-outperforming-larger/)**Cheng-Yu Hsieh, Chun-Liang Li, Chih-kuan Yeh et al.*307 citations · our summary*
4. **[Measuring and Narrowing the Compositionality Gap in Language Models](https://aclanthology.org/2023.findings-emnlp.378/)**Ofir Press, Muru Zhang, Sewon Min et al.*277 citations*
5. **[Towards Mitigating LLM Hallucination via Self Reflection](https://md.research.elamur.ai/free/en/papers/ji-2023-mitigating-llm-hallucination-self-reflection/)**Ziwei Ji, Tiezheng Yu, Yan Xu et al.*253 citations · our summary*
6. **[Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them](https://md.research.elamur.ai/free/en/papers/suzgun-2023-challenging-big-bench-tasks-whether/)**Mirac Suzgun, Nathan Scales, Nathanael Schärli et al.*243 citations · our summary*
7. **[ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learning](https://md.research.elamur.ai/free/en/papers/lai-2023-chatgpt-beyond-english-comprehensive-evaluation/)**Viet Dac Lai, Nghia Ngo, Amir Pouran Ben Veyseh et al.*228 citations · our summary*
8. **[HuatuoGPT, Towards Taming Language Model to Be a Doctor](https://md.research.elamur.ai/free/en/papers/zhang-2023-huatuogpt-taming-language-model-be/)**Hongbo Zhang, Junying Chen, Feng Jiang et al.*206 citations · our summary*
9. **[Text Classification via Large Language Models](https://md.research.elamur.ai/free/en/papers/sun-2023-text-classification-large-language-models/)**Xiaofei Sun, Xiaoya Li, Jiwei Li et al.*199 citations · our summary*
10. **[Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergy](https://md.research.elamur.ai/free/en/papers/shao-2023-enhancing-retrieval-augmented-large-language/)**Zhihong Shao, Yeyun Gong, Yelong Shen et al.*192 citations · our summary*
11. **[Multi-step Jailbreaking Privacy Attacks on ChatGPT](https://md.research.elamur.ai/free/en/papers/li-2023-multi-step-jailbreaking-privacy-attacks/)**Haoran Li, Dadi Guo, Wei Fan et al.*187 citations · our summary*
12. **[SpeechGPT: Empowering Large Language Models with Intrinsic Cross-Modal Conversational Abilities](https://md.research.elamur.ai/free/en/papers/zhang-2023-speechgpt-empowering-large-language-models/)**Dong Zhang, Shimin Li, Xin Zhang et al.*187 citations · our summary*
13. **[Discovering Language Model Behaviors with Model-Written Evaluations](https://aclanthology.org/2023.findings-acl.847/)**Ethan Perez, Sam Ringer, Kamile Lukosiute et al.*183 citations*
14. **[Toxicity in chatgpt: Analyzing persona-assigned language models](https://md.research.elamur.ai/free/en/papers/deshpande-2023-toxicity-chatgpt-analyzing-persona-assigned/)**Ameet Deshpande, Vishvak Murahari, Tanmay Rajpurohit et al.*170 citations · our summary*
15. **[PubMedCLIP: How Much Does CLIP Benefit Visual Question Answering in the Medical Domain?](https://aclanthology.org/2023.findings-eacl.88/)**Sedigheh Eslami, Christoph Meinel, Gerard de Melo*167 citations*
16. **[The Internal State of an LLM Knows When It's Lying](https://md.research.elamur.ai/free/en/papers/azaria-2023-internal-state-llm-knows-when/)**Amos Azaria, Tom Mitchell*164 citations · our summary*
17. **[Why Can GPT Learn In-Context? Language Models Secretly Perform Gradient Descent as Meta-Optimizers](https://md.research.elamur.ai/free/en/papers/dai-2023-why-can-gpt-learn-context/)**Damai Dai, Yutao Sun, Li Dong et al.*147 citations · our summary*
18. **[Logic-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoning](https://md.research.elamur.ai/free/en/papers/pan-2023-logic-lm-empowering-large-language/)**Liangming Pan, Alon Albalak, Xinyi Wang et al.*143 citations · our summary*
19. **[Evaluating Verifiability in Generative Search Engines](https://md.research.elamur.ai/free/en/papers/liu-2023-evaluating-verifiability-generative-search-engines/)**Nelson Liu, Tianyi Zhang, Percy Liang*137 citations · our summary*
20. **[Sources of Hallucination by Large Language Models on Inference Tasks](https://md.research.elamur.ai/free/en/papers/mckenna-2023-sources-hallucination-large-language-models/)**Nick McKenna, Tianyi Li, Liang Cheng et al.*136 citations · our summary*
21. **[“Kelly is a Warm Person, Joseph is a Role Model”: Gender Biases in LLM-Generated Reference Letters](https://md.research.elamur.ai/free/en/papers/wan-2023-kelly-is-warm-person-joseph/)**Yixin Wan, George Pu, Jiao Sun et al.*136 citations · our summary*
22. **[One Embedder, Any Task: Instruction-Finetuned Text Embeddings](https://aclanthology.org/2023.findings-acl.71/)**Hongjin Su, Weijia Shi, Jungo Kasai et al.*131 citations*
23. **[Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!](https://md.research.elamur.ai/free/en/papers/ma-2023-large-language-model-is-not/)**Yubo Ma, Yixin Cao, Yong Hong et al.*113 citations · our summary*
24. **[Large Language Models are Better Reasoners with Self-Verification](https://md.research.elamur.ai/free/en/papers/weng-2023-large-language-models-are-better/)**Yixuan Weng, Minjun Zhu, Fei Xia et al.*107 citations · our summary*
25. **[LLM-in-the-loop: Leveraging Large Language Model for Thematic Analysis](https://aclanthology.org/2023.findings-emnlp.669/)**Shih-Chieh Dai, Aiping Xiong, Lun-Wei Ku*106 citations*

[See all 2,194 papers in Findings of the Association for Computational Linguistics 2023 — accepted papers →](https://md.research.elamur.ai/free/en/venues/findings/2023/papers/)

## Papers with our summary in our library (95)

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

1. **[Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them](https://md.research.elamur.ai/free/en/papers/suzgun-2023-challenging-big-bench-tasks-whether/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mirac Suzgun, Nathan Scales, Nathanael Schärli, et al.*2023 · 1,096 citations*
2. **[Towards Reasoning in Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/huang-2023-reasoning-large-language-models-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jie Huang, Kevin Chen-Chuan Chang*2023 · 778 citations*
3. **[Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes](https://md.research.elamur.ai/free/en/papers/hsieh-2023-distilling-step-step-outperforming-larger/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cheng-Yu Hsieh, Chun-Liang Li, Chih-kuan Yeh, et al.*2023 · 685 citations*
4. **[Sentiment Analysis in the Era of Large Language Models: A Reality Check](https://md.research.elamur.ai/free/en/papers/zhang-2023-sentiment-analysis-era-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenxuan Zhang, Yue Deng, Bing Liu, et al.*2023 · 505 citations*
5. **[The Internal State of an LLM Knows When It's Lying](https://md.research.elamur.ai/free/en/papers/azaria-2023-internal-state-llm-knows-when/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Amos Azaria, Tom Mitchell*2023 · 427 citations*
6. **[ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learning](https://md.research.elamur.ai/free/en/papers/lai-2023-chatgpt-beyond-english-comprehensive-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Viet Dac Lai, Nghia Ngo, Amir Pouran Ben Veyseh, et al.*2023 · 421 citations*
7. **[Towards Mitigating LLM Hallucination via Self Reflection](https://md.research.elamur.ai/free/en/papers/ji-2023-mitigating-llm-hallucination-self-reflection/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ziwei Ji, Tiezheng Yu, Yan Xu, et al.*2023 · 352 citations*
8. **[Toxicity in chatgpt: Analyzing persona-assigned language models](https://md.research.elamur.ai/free/en/papers/deshpande-2023-toxicity-chatgpt-analyzing-persona-assigned/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ameet Deshpande, Vishvak Murahari, Tanmay Rajpurohit, et al.*2023 · 346 citations*
9. **[SpeechGPT: Empowering Large Language Models with Intrinsic Cross-Modal Conversational Abilities](https://md.research.elamur.ai/free/en/papers/zhang-2023-speechgpt-empowering-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dong Zhang, Shimin Li, Xin Zhang, et al.*2023 · 346 citations*
10. **[Large Language Models are Better Reasoners with Self-Verification](https://md.research.elamur.ai/free/en/papers/weng-2023-large-language-models-are-better/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yixuan Weng, Minjun Zhu, Fei Xia, et al.*2023 · 302 citations*
11. **[Multi-step Jailbreaking Privacy Attacks on ChatGPT](https://md.research.elamur.ai/free/en/papers/li-2023-multi-step-jailbreaking-privacy-attacks/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haoran Li, Dadi Guo, Wei Fan, et al.*2023 · 300 citations*
12. **[Evaluating Verifiability in Generative Search Engines](https://md.research.elamur.ai/free/en/papers/liu-2023-evaluating-verifiability-generative-search-engines/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nelson Liu, Tianyi Zhang, Percy Liang*2023 · 294 citations*
13. **[Text Classification via Large Language Models](https://md.research.elamur.ai/free/en/papers/sun-2023-text-classification-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaofei Sun, Xiaoya Li, Jiwei Li, et al.*2023 · 292 citations*
14. **[HuatuoGPT, Towards Taming Language Model to Be a Doctor](https://md.research.elamur.ai/free/en/papers/zhang-2023-huatuogpt-taming-language-model-be/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hongbo Zhang, Junying Chen, Feng Jiang, et al.*2023 · 282 citations*
15. **[Large Language Models Sensitivity to The Order of Options in Multiple-Choice Questions](https://md.research.elamur.ai/free/en/papers/pezeshkpour-2023-large-language-models-sensitivity-order/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Pouya Pezeshkpour, Estevam Hruschka*2023 · 256 citations*
16. **[Why Can GPT Learn In-Context? Language Models Secretly Perform Gradient Descent as Meta-Optimizers](https://md.research.elamur.ai/free/en/papers/dai-2023-why-can-gpt-learn-context/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Damai Dai, Yutao Sun, Li Dong, et al.*2023 · 253 citations*
17. **[NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each Benchmark](https://md.research.elamur.ai/free/en/papers/sainz-2023-nlp-evaluation-trouble-need-measure/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Oscar Sainz, Jon Campos, Iker García-Ferrero, et al.*2023 · 245 citations*
18. **[In-context Examples Selection for Machine Translation](https://md.research.elamur.ai/free/en/papers/agrawal-2023-context-examples-selection-machine-translation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sweta Agrawal, Chunting Zhou, Mike Lewis, et al.*2023 · 242 citations*
19. **[Distilling Reasoning Capabilities into Smaller Language Models](https://md.research.elamur.ai/free/en/papers/shridhar-2023-distilling-reasoning-capabilities-into-smaller/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kumar Shridhar, Alessandro Stolfo, Mrinmaya Sachan*2023 · 217 citations*
20. **[Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!](https://md.research.elamur.ai/free/en/papers/ma-2023-large-language-model-is-not/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yubo Ma, Yixin Cao, Yong Hong, et al.*2023 · 211 citations*
21. **[Sources of Hallucination by Large Language Models on Inference Tasks](https://md.research.elamur.ai/free/en/papers/mckenna-2023-sources-hallucination-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nick McKenna, Tianyi Li, Liang Cheng, et al.*2023 · 209 citations*
22. **[“Kelly is a Warm Person, Joseph is a Role Model”: Gender Biases in LLM-Generated Reference Letters](https://md.research.elamur.ai/free/en/papers/wan-2023-kelly-is-warm-person-joseph/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yixin Wan, George Pu, Jiao Sun, et al.*2023 · 206 citations*
23. **[A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets](https://md.research.elamur.ai/free/en/papers/laskar-2023-systematic-study-comprehensive-evaluation-chatgpt/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.*2023 · 200 citations*
24. **[Towards Making the Most of ChatGPT for Machine Translation](https://md.research.elamur.ai/free/en/papers/peng-2023-making-most-chatgpt-machine-translation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Keqin Peng, Liang Ding, Qihuang Zhong, et al.*2023 · 190 citations*
25. **[Large Language Models are few(1)-shot Table Reasoners](https://md.research.elamur.ai/free/en/papers/chen-2023-large-language-models-are-few/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenhu Chen*2023 · 182 citations*

[See all 95 works in Findings of the Association for Computational Linguistics 2023 — accepted papers →](https://md.research.elamur.ai/free/en/venues/findings/2023/works/)

## Top topics

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

[Language models & pretraining (39)](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning (14)](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Evaluation & benchmarks (12)](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Dialogue systems (7)](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [Sentiment & emotion (6)](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · [Semitic languages (6)](https://md.research.elamur.ai/free/en/topics/semitic-languages/) · [Discourse analysis (5)](https://md.research.elamur.ai/free/en/topics/discourse-analysis/) · [Multilingual & cross-lingual NLP (5)](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/) · [Hebrew & Aramaic (5)](https://md.research.elamur.ai/free/en/topics/hebrew-aramaic/) · [Bias, fairness & safety (5)](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [English (5)](https://md.research.elamur.ai/free/en/topics/english/) · [Modern Hebrew (5)](https://md.research.elamur.ai/free/en/topics/modern-hebrew/) · [Coreference resolution (4)](https://md.research.elamur.ai/free/en/topics/coreference-resolution/) · [Machine translation (4)](https://md.research.elamur.ai/free/en/topics/machine-translation/) · [Information retrieval & search (4)](https://md.research.elamur.ai/free/en/topics/information-retrieval/)

**16 more topics**

[Vision & language (4)](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Speech act theory (2)](https://md.research.elamur.ai/free/en/topics/speech-act-theory/) · [Question answering (2)](https://md.research.elamur.ai/free/en/topics/question-answering/) · [Speech & spoken language (2)](https://md.research.elamur.ai/free/en/topics/speech/) · [Word sense disambiguation (1)](https://md.research.elamur.ai/free/en/topics/word-sense-disambiguation/) · [Semantic role labeling (1)](https://md.research.elamur.ai/free/en/topics/semantic-role-labeling/) · [Summarization (1)](https://md.research.elamur.ai/free/en/topics/summarization/) · [Text generation (1)](https://md.research.elamur.ai/free/en/topics/text-generation/) · [Low-resource languages (1)](https://md.research.elamur.ai/free/en/topics/low-resource-languages/) · [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/) · [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/) · [Interpretability (1)](https://md.research.elamur.ai/free/en/topics/interpretability/) · [Efficient models & compression (1)](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Idioms & multiword expressions (1)](https://md.research.elamur.ai/free/en/topics/multiword-expressions/)

## Fields

[Computer Science (95)](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities (90)](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Social Sciences (12)](https://md.research.elamur.ai/free/en/shelves/social-sciences/) · [Psychology (4)](https://md.research.elamur.ai/free/en/shelves/psychology/) · [Medicine (2)](https://md.research.elamur.ai/free/en/shelves/medicine/)

## Top authors

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

[🧑‍🔬**Reut Tsarfaty**4 works here · 26 citations](https://md.research.elamur.ai/free/en/authors/reut-tsarfaty/) · [🧑‍🔬**Mrinmaya Sachan**3 works here · 509 citations](https://md.research.elamur.ai/free/en/authors/mrinmaya-sachan/) · [🧑‍🔬**Wenhu Chen**3 works here · 480 citations](https://md.research.elamur.ai/free/en/authors/wenhu-chen/) · [🧑‍🔬**Hyung Won Chung**2 works here · 1,175 citations](https://md.research.elamur.ai/free/en/authors/hyung-won-chung/) · [🧑‍🔬**Yi Tay**2 works here · 1,175 citations](https://md.research.elamur.ai/free/en/authors/yi-tay/) · [🧑‍🔬**Jie Huang**2 works here · 1,078 citations](https://md.research.elamur.ai/free/en/authors/jie-huang/) · [🧑‍🔬**Lidong Bing**2 works here · 624 citations](https://md.research.elamur.ai/free/en/authors/lidong-bing/) · [🧑‍🔬**Xipeng Qiu**2 works here · 424 citations](https://md.research.elamur.ai/free/en/authors/xipeng-qiu/) · [🧑‍🔬**Furu Wei**2 works here · 355 citations](https://md.research.elamur.ai/free/en/authors/furu-wei/) · [🧑‍🔬**Zhifang Sui**2 works here · 355 citations](https://md.research.elamur.ai/free/en/authors/zhifang-sui/) · [🧑‍🔬**Preslav Nakov**2 works here · 349 citations](https://md.research.elamur.ai/free/en/authors/preslav-nakov/) · [🧑‍🔬**Yangqiu Song**2 works here · 345 citations](https://md.research.elamur.ai/free/en/authors/yangqiu-song/)

## Top institutions

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

[🎓**Nanyang Technological University** Singapore · Singapore 7 works here](https://md.research.elamur.ai/free/en/universities/nanyang-technological-university/) · [🎓**Hong Kong University of Science and Technology** Hong Kong · China 6 works here](https://md.research.elamur.ai/free/en/universities/hong-kong-university-of-science-and-technology/) · [🎓**Stanford University** Stanford · United States 6 works here](https://md.research.elamur.ai/free/en/universities/stanford-university/) · [🏢**Google** Mountain View · United States 5 works here](https://md.research.elamur.ai/free/en/companies/google/) · [🎓**Bar-Ilan University** Ramat Gan · Israel 4 works here](https://md.research.elamur.ai/free/en/universities/bar-ilan-university/) · [🎓**University of Washington** Seattle · United States 4 works here](https://md.research.elamur.ai/free/en/universities/university-of-washington/) · [🎓**Harbin Institute of Technology** Harbin · China 4 works here](https://md.research.elamur.ai/free/en/universities/harbin-institute-of-technology/) · [🔬**Allen Institute for Artificial Intelligence** Seattle · United States 4 works here](https://md.research.elamur.ai/free/en/labs/allen-institute-for-artificial-intelligence/) · [🎓**University of Southern California** Los Angeles · United States 3 works here](https://md.research.elamur.ai/free/en/universities/university-of-southern-california/) · [🏢**Microsoft** Redmond · United States 3 works here](https://md.research.elamur.ai/free/en/companies/microsoft/) · [🎓**University of Waterloo** Waterloo · Canada 3 works here](https://md.research.elamur.ai/free/en/universities/university-of-waterloo/) · [🎓**University of Illinois Urbana-Champaign** Urbana · United States 3 works here](https://md.research.elamur.ai/free/en/universities/university-of-illinois-urbana-champaign/)

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

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