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title: "Findings of the Association for Computational Linguistics"
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# Findings of the Association for Computational Linguistics 2024 — accepted papers

Findings of the Association for Computational Linguistics 2024 is the 2024 edition of the Findings of the Association for Computational Linguistics, held in Bangkok, Thailand, August 2024 (publisher: Association for Computational Linguistics). The ACL Anthology lists 2,432 papers of it; our library holds 63 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

[**2,432** papers in the proceedings](#all) · [**63** works in our library](https://md.research.elamur.ai/free/en/venues/findings/2024/works/) · [**7,586** citations of these works](https://md.research.elamur.ai/free/en/venues/findings/2024/works/)**Bangkok, Thailand** where it was held**August 2024** when

## Most cited papers

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

1. **[M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation](https://md.research.elamur.ai/free/en/papers/chen-2024-m3-embedding-multi-linguality/)**Jianlyu Chen, Shitao Xiao, Peitian Zhang et al.*700 citations · our summary*
2. **[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/)**Wenxuan Zhang, Yue Deng, Bing Liu et al.*359 citations · our summary*
3. **[Benchmarking Retrieval-Augmented Generation for Medicine](https://md.research.elamur.ai/free/en/papers/xiong-2024-benchmarking-retrieval-augmented-generation-medicine/)**Guangzhi Xiong, Qiao Jin, Zhiyong Lu et al.*299 citations · our summary*
4. **[Chain-of-Verification Reduces Hallucination in Large Language Models](https://aclanthology.org/2024.findings-acl.212/)**Shehzaad Dhuliawala, Mojtaba Komeili, Jing Xu et al.*253 citations*
5. **[BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains](https://md.research.elamur.ai/free/en/papers/labrak-2024-biomistral-collection-open-source-pretrained/)**Yanis Labrak, Adrien Bazoge, Emmanuel Morin et al.*250 citations · our summary*
6. **[MM-LLMs: Recent Advances in MultiModal Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-mm-llms-recent-advances-multimodal/)**Duzhen Zhang, Yahan Yu, Jiahua Dong et al.*250 citations · our summary*
7. **[AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models](https://md.research.elamur.ai/free/en/papers/zhong-2024-agieval-human-centric-benchmark-evaluating/)**Wanjun Zhong, Ruixiang Cui, Yiduo Guo et al.*199 citations · our summary*
8. **[The Effect of Sampling Temperature on Problem Solving in Large Language Models](https://md.research.elamur.ai/free/en/papers/renze-2024-effect-sampling-temperature-problem-solving/)**Matthew Renze*198 citations · our summary*
9. **[Multilingual Machine Translation with Large Language Models: Empirical Results and Analysis](https://md.research.elamur.ai/free/en/papers/zhu-2024-multilingual-machine-translation-large-language/)**Wenhao Zhu, Hongyi Liu, Qingxiu Dong et al.*181 citations · our summary*
10. **[Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting](https://md.research.elamur.ai/free/en/papers/qin-2024-large-language-models-are-effective/)**Zhen Qin, Rolf Jagerman, Kai Hui et al.*154 citations · our summary*

## All accepted papers (2,432)

The most cited first; 63 with our summary link to their page here, the others to the original.

1. **[M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation](https://md.research.elamur.ai/free/en/papers/chen-2024-m3-embedding-multi-linguality/)**Jianlyu Chen, Shitao Xiao, Peitian Zhang et al.*700 citations · our summary*
2. **[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/)**Wenxuan Zhang, Yue Deng, Bing Liu et al.*359 citations · our summary*
3. **[Benchmarking Retrieval-Augmented Generation for Medicine](https://md.research.elamur.ai/free/en/papers/xiong-2024-benchmarking-retrieval-augmented-generation-medicine/)**Guangzhi Xiong, Qiao Jin, Zhiyong Lu et al.*299 citations · our summary*
4. **[Chain-of-Verification Reduces Hallucination in Large Language Models](https://aclanthology.org/2024.findings-acl.212/)**Shehzaad Dhuliawala, Mojtaba Komeili, Jing Xu et al.*253 citations*
5. **[BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains](https://md.research.elamur.ai/free/en/papers/labrak-2024-biomistral-collection-open-source-pretrained/)**Yanis Labrak, Adrien Bazoge, Emmanuel Morin et al.*250 citations · our summary*
6. **[MM-LLMs: Recent Advances in MultiModal Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-mm-llms-recent-advances-multimodal/)**Duzhen Zhang, Yahan Yu, Jiahua Dong et al.*250 citations · our summary*
7. **[AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models](https://md.research.elamur.ai/free/en/papers/zhong-2024-agieval-human-centric-benchmark-evaluating/)**Wanjun Zhong, Ruixiang Cui, Yiduo Guo et al.*199 citations · our summary*
8. **[The Effect of Sampling Temperature on Problem Solving in Large Language Models](https://md.research.elamur.ai/free/en/papers/renze-2024-effect-sampling-temperature-problem-solving/)**Matthew Renze*198 citations · our summary*
9. **[Multilingual Machine Translation with Large Language Models: Empirical Results and Analysis](https://md.research.elamur.ai/free/en/papers/zhu-2024-multilingual-machine-translation-large-language/)**Wenhao Zhu, Hongyi Liu, Qingxiu Dong et al.*181 citations · our summary*
10. **[Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting](https://md.research.elamur.ai/free/en/papers/qin-2024-large-language-models-are-effective/)**Zhen Qin, Rolf Jagerman, Kai Hui et al.*154 citations · our summary*
11. **[emotion2vec: Self-Supervised Pre-Training for Speech Emotion Representation](https://aclanthology.org/2024.findings-acl.931/)**Ziyang Ma, Zhisheng Zheng, Jiaxin Ye et al.*150 citations*
12. **[MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning](https://md.research.elamur.ai/free/en/papers/tang-2024-medagents-large-language-models-as/)**Xiangru Tang, Anni Zou, Zhuosheng Zhang et al.*149 citations · our summary*
13. **[LLM-Rec: Personalized Recommendation via Prompting Large Language Models](https://aclanthology.org/2024.findings-naacl.39/)**Hanjia Lyu, Song Jiang, Hanqing Zeng et al.*142 citations*
14. **[Aligning Large Multimodal Models with Factually Augmented RLHF](https://aclanthology.org/2024.findings-acl.775/)**Zhiqing Sun, Sheng Shen, Shengcao Cao et al.*134 citations*
15. **[LLM-QAT: Data-Free Quantization Aware Training for Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2024-llm-qat-data-free-quantization/)**Zechun Liu, Barlas Oguz, Changsheng Zhao et al.*127 citations · our summary*
16. **[InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents](https://md.research.elamur.ai/free/en/papers/zhan-2024-injecagent-benchmarking-indirect-prompt-injections/)**Qiusi Zhan, Zhixiang Liang, Zifan Ying et al.*124 citations · our summary*
17. **[On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey](https://md.research.elamur.ai/free/en/papers/long-2024-llms-driven-synthetic-data-generation/)**Lin Long, Rui Wang, Ruixuan Xiao et al.*123 citations · our summary*
18. **[PersonaLLM: Investigating the Ability of Large Language Models to Express Personality Traits](https://aclanthology.org/2024.findings-naacl.229/)**Hang Jiang, Xiajie Zhang, Xubo Cao et al.*118 citations*
19. **[RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models](https://aclanthology.org/2024.findings-acl.878/)**Noah Wang, Z.Y. Peng, Haoran Que et al.*111 citations*
20. **[The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG)](https://aclanthology.org/2024.findings-acl.267/)**Shenglai Zeng, Jiankun Zhang, Pengfei He et al.*102 citations*
21. **[CMMLU: Measuring massive multitask language understanding in Chinese](https://md.research.elamur.ai/free/en/papers/li-2023-cmmlu-measuring-massive-multitask-language/)**Haonan Li, Yixuan Zhang, Fajri Koto et al.*100 citations · our summary*
22. **[Data Augmentation using LLMs: Data Perspectives, Learning Paradigms and Challenges](https://aclanthology.org/2024.findings-acl.97/)**Bosheng Ding, Chengwei Qin, Ruochen Zhao et al.*98 citations*
23. **[Prompt Engineering a Prompt Engineer](https://aclanthology.org/2024.findings-acl.21/)**Qinyuan Ye, Mohamed Ahmed, Reid Pryzant et al.*97 citations*
24. **[The Revolution of Multimodal Large Language Models: A Survey](https://aclanthology.org/2024.findings-acl.807/)**Davide Caffagni, Federico Cocchi, Luca Barsellotti et al.*89 citations*
25. **[Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalization](https://md.research.elamur.ai/free/en/papers/tseng-2024-two-tales-persona-llms-survey/)**Yu-Min Tseng, Yu-Chao Huang, Teng-Yun Hsiao et al.*85 citations · our summary*

[See all 2,432 papers in Findings of the Association for Computational Linguistics 2024 — accepted papers →](https://md.research.elamur.ai/free/en/venues/findings/2024/papers/)

## Papers with our summary in our library (63)

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

1. **[AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models](https://md.research.elamur.ai/free/en/papers/zhong-2024-agieval-human-centric-benchmark-evaluating/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wanjun Zhong, Ruixiang Cui, Yiduo Guo, et al.*2024 · 564 citations*
2. **[Multilingual Machine Translation with Large Language Models: Empirical Results and Analysis](https://md.research.elamur.ai/free/en/papers/zhu-2024-multilingual-machine-translation-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenhao Zhu, Hongyi Liu, Qingxiu Dong, et al.*2024 · 503 citations*
3. **[Benchmarking Retrieval-Augmented Generation for Medicine](https://md.research.elamur.ai/free/en/papers/xiong-2024-benchmarking-retrieval-augmented-generation-medicine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guangzhi Xiong, Qiao Jin, Zhiyong Lu, et al.*2024 · 426 citations*
4. **[BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains](https://md.research.elamur.ai/free/en/papers/labrak-2024-biomistral-collection-open-source-pretrained/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yanis Labrak, Adrien Bazoge, Emmanuel Morin, et al.*2024 · 408 citations*
5. **[MM-LLMs: Recent Advances in MultiModal Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-mm-llms-recent-advances-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Duzhen Zhang, Yahan Yu, Jiahua Dong, et al.*2024 · 318 citations*
6. **[Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting](https://md.research.elamur.ai/free/en/papers/qin-2024-large-language-models-are-effective/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhen Qin, Rolf Jagerman, Kai Hui, et al.*2024 · 297 citations*
7. **[LLM-QAT: Data-Free Quantization Aware Training for Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2024-llm-qat-data-free-quantization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zechun Liu, Barlas Oguz, Changsheng Zhao, et al.*2024 · 275 citations*
8. **[The Effect of Sampling Temperature on Problem Solving in Large Language Models](https://md.research.elamur.ai/free/en/papers/renze-2024-effect-sampling-temperature-problem-solving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Matthew Renze*2024 · 262 citations*
9. **[MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning](https://md.research.elamur.ai/free/en/papers/tang-2024-medagents-large-language-models-as/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiangru Tang, Anni Zou, Zhuosheng Zhang, et al.*2024 · 245 citations*
10. **[On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey](https://md.research.elamur.ai/free/en/papers/long-2024-llms-driven-synthetic-data-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lin Long, Rui Wang, Ruixuan Xiao, et al.*2024 · 236 citations*
11. **[InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Large Language Model Agents](https://md.research.elamur.ai/free/en/papers/zhan-2024-injecagent-benchmarking-indirect-prompt-injections/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiusi Zhan, Zhixiang Liang, Zifan Ying, et al.*2024 · 187 citations*
12. **[Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalization](https://md.research.elamur.ai/free/en/papers/tseng-2024-two-tales-persona-llms-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yu-Min Tseng, Yu-Chao Huang, Teng-Yun Hsiao, et al.*2024 · 177 citations*
13. **[LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression](https://md.research.elamur.ai/free/en/papers/pan-2024-llmlingua-2-data-distillation-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuoshi Pan, Qianhui Wu, Huiqiang Jiang, et al.*2024 · 159 citations*
14. **[Unlocking Efficiency in Large Language Model Inference: A Comprehensive Survey of Speculative Decoding](https://md.research.elamur.ai/free/en/papers/xia-2024-unlocking-efficiency-large-language-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Heming Xia, Zhe Yang, Qingxiu Dong, et al.*2024 · 145 citations*
15. **[Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts](https://md.research.elamur.ai/free/en/papers/wang-2024-interpretable-preferences-multi-objective-reward/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haoxiang Wang, Wei Xiong, Tengyang Xie, et al.*2024 · 142 citations*
16. **[Error Analysis Prompting Enables Human-Like Translation Evaluation in Large Language Models](https://md.research.elamur.ai/free/en/papers/lu-2024-error-analysis-prompting-enables-human/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qingyu Lu, Baopu Qiu, Liang Ding, et al.*2024 · 135 citations*
17. **[InFoBench: Evaluating Instruction Following Ability in Large Language Models](https://md.research.elamur.ai/free/en/papers/qin-2024-infobench-evaluating-instruction-following-ability/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yiwei Qin, Kaiqiang Song, Yebowen Hu, et al.*2024 · 133 citations*
18. **[Scaling Sentence Embeddings with Large Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2024-scaling-sentence-embeddings-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ting Jiang, Shaohan Huang, Zhongzhi Luan, et al.*2024 · 126 citations*
19. **[The Impact of Reasoning Step Length on Large Language Models](https://md.research.elamur.ai/free/en/papers/jin-2024-impact-reasoning-step-length-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mingyu Jin, Qinkai Yu, Dong Shu, et al.*2024 · 119 citations*
20. **[ArabicMMLU: Assessing Massive Multitask Language Understanding in Arabic](https://md.research.elamur.ai/free/en/papers/koto-2024-arabicmmlu-assessing-massive-multitask-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fajri Koto, Haonan Li, Sara Shatnawi, et al.*2024 · 116 citations*
21. **[SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-salad-bench-hierarchical-comprehensive-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lijun Li, Bowen Dong, Ruohui Wang, et al.*2024 · 114 citations*
22. **[mPLUG-DocOwl 1.5: Unified Structure Learning for OCR-free Document Understanding](https://md.research.elamur.ai/free/en/papers/hu-2024-mplug-docowl-1-5-unified/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Anwen Hu, Haiyang Xu, Jiabo Ye, et al.*2024 · 109 citations*
23. **[Tokenizer Choice For LLM Training: Negligible or Crucial?](https://md.research.elamur.ai/free/en/papers/ali-2024-tokenizer-choice-llm-training-negligible/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mehdi Ali, Michael Fromm, Klaudia Thellmann, et al.*2024 · 102 citations*
24. **[Disentangling Length from Quality in Direct Preference Optimization](https://md.research.elamur.ai/free/en/papers/park-2024-disentangling-length-quality-direct-preference/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ryan Park, Rafael Rafailov, Stefano Ermon, et al.*2024 · 99 citations*
25. **[Unsupervised Real-Time Hallucination Detection based on the Internal States of Large Language Models](https://md.research.elamur.ai/free/en/papers/su-2024-unsupervised-real-time-hallucination-detection/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weihang Su, Changyue Wang, Qingyao Ai, et al.*2024 · 98 citations*

[See all 63 works in Findings of the Association for Computational Linguistics 2024 — accepted papers →](https://md.research.elamur.ai/free/en/venues/findings/2024/works/)

## Top topics

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

[Language models & pretraining (25)](https://md.research.elamur.ai/free/en/topics/language-models/) · [Evaluation & benchmarks (8)](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Reasoning (7)](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Multilingual & cross-lingual NLP (6)](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/) · [Semitic languages (6)](https://md.research.elamur.ai/free/en/topics/semitic-languages/) · [Bias, fairness & safety (5)](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Hebrew & Aramaic (4)](https://md.research.elamur.ai/free/en/topics/hebrew-aramaic/) · [Vision & language (4)](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Efficient models & compression (4)](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Discourse analysis (3)](https://md.research.elamur.ai/free/en/topics/discourse-analysis/) · [Machine translation (3)](https://md.research.elamur.ai/free/en/topics/machine-translation/) · [English (3)](https://md.research.elamur.ai/free/en/topics/english/) · [Implicature (2)](https://md.research.elamur.ai/free/en/topics/implicature/) · [Information retrieval & search (2)](https://md.research.elamur.ai/free/en/topics/information-retrieval/) · [Biblical Hebrew (2)](https://md.research.elamur.ai/free/en/topics/biblical-hebrew/)

**12 more topics**

[Aramaic (2)](https://md.research.elamur.ai/free/en/topics/aramaic/) · [Coreference resolution (1)](https://md.research.elamur.ai/free/en/topics/coreference-resolution/) · [Sentiment & emotion (1)](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · [Summarization (1)](https://md.research.elamur.ai/free/en/topics/summarization/) · [Text generation (1)](https://md.research.elamur.ai/free/en/topics/text-generation/) · [Dialogue systems (1)](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [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/) · [Tokenization & segmentation (1)](https://md.research.elamur.ai/free/en/topics/tokenization/) · [French (1)](https://md.research.elamur.ai/free/en/topics/french/) · [Modern Hebrew (1)](https://md.research.elamur.ai/free/en/topics/modern-hebrew/)

## Fields

[Computer Science (63)](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities (60)](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Social Sciences (7)](https://md.research.elamur.ai/free/en/shelves/social-sciences/) · [Medicine (3)](https://md.research.elamur.ai/free/en/shelves/medicine/) · [Engineering (1)](https://md.research.elamur.ai/free/en/shelves/engineering/) · [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.

[🧑‍🔬**Zhuosheng Zhang**3 works here · 422 citations](https://md.research.elamur.ai/free/en/authors/zhuosheng-zhang/) · [🧑‍🔬**Haonan Li**3 works here · 302 citations](https://md.research.elamur.ai/free/en/authors/haonan-li/) · [🧑‍🔬**Preslav Nakov**3 works here · 302 citations](https://md.research.elamur.ai/free/en/authors/preslav-nakov/) · [🧑‍🔬**Reut Tsarfaty**3 works here · 93 citations](https://md.research.elamur.ai/free/en/authors/reut-tsarfaty/) · [🧑‍🔬**Qingxiu Dong**2 works here · 648 citations](https://md.research.elamur.ai/free/en/authors/qingxiu-dong/) · [🧑‍🔬**Dong Yu**2 works here · 451 citations](https://md.research.elamur.ai/free/en/authors/dong-yu/) · [🧑‍🔬**Rui Wang**2 works here · 333 citations](https://md.research.elamur.ai/free/en/authors/rui-wang/) · [🧑‍🔬**Yu Meng**2 works here · 266 citations](https://md.research.elamur.ai/free/en/authors/yu-meng/) · [🧑‍🔬**Timothy Baldwin**2 works here · 186 citations](https://md.research.elamur.ai/free/en/authors/timothy-baldwin/) · [🧑‍🔬**Dahua Lin**2 works here · 177 citations](https://md.research.elamur.ai/free/en/authors/dahua-lin/) · [🧑‍🔬**Yujia Zhou**2 works here · 126 citations](https://md.research.elamur.ai/free/en/authors/yujia-zhou/) · [🧑‍🔬**Nizar Habash**2 works here · 120 citations](https://md.research.elamur.ai/free/en/authors/nizar-habash/)

## Top institutions

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

[🎓**Shanghai Jiao Tong University** Shanghai · China 6 works here](https://md.research.elamur.ai/free/en/universities/shanghai-jiao-tong-university/) · [🎓**University of Illinois Urbana-Champaign** Urbana · United States 3 works here](https://md.research.elamur.ai/free/en/universities/university-of-illinois-urbana-champaign/) · [🎓**The University of Melbourne** Melbourne · Australia 3 works here](https://md.research.elamur.ai/free/en/universities/the-university-of-melbourne/) · [🎓**Harbin Institute of Technology** Harbin · China 3 works here](https://md.research.elamur.ai/free/en/universities/harbin-institute-of-technology/) · [🎓**Mohamed bin Zayed University of Artificial Intelligence** Abu Dhabi · United Arab Emirates 3 works here](https://md.research.elamur.ai/free/en/universities/mohamed-bin-zayed-university-of-artificial-intelligence/) · [🔬**Shanghai Artificial Intelligence Laboratory** Shanghai · China 3 works here](https://md.research.elamur.ai/free/en/labs/shanghai-artificial-intelligence-laboratory/) · [🎓**University of Pennsylvania** Philadelphia · United States 3 works here](https://md.research.elamur.ai/free/en/universities/university-of-pennsylvania/) · [🎓**New York University Abu Dhabi** Abu Dhabi · United Arab Emirates 2 works here](https://md.research.elamur.ai/free/en/universities/new-york-university-abu-dhabi/) · [🎓**Beijing Institute of Technology** Beijing · China 2 works here](https://md.research.elamur.ai/free/en/universities/beijing-institute-of-technology/) · [🏢**Microsoft** Redmond · United States 2 works here](https://md.research.elamur.ai/free/en/companies/microsoft/) · [🏢**Google** Mountain View · United States 2 works here](https://md.research.elamur.ai/free/en/companies/google/) · [🎓**Bar-Ilan University** Ramat Gan · Israel 2 works here](https://md.research.elamur.ai/free/en/universities/bar-ilan-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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