🧑‍🔬 Who cites Dan Shi

118 citations of their works from 118 papers of our library (of the 149,439 whose bibliographies we read) · 22 with a page here, the most cited first · ← Dan Shi

1. LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation MethodsarXiv:2412.05579Haitao Li, Qian Dong, Junjie Chen, et al.2024 · 195 citations
2. PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning OptimizationarXiv:2306.05087Yidong Wang, Zhuohao Yu, Zhengran Zeng, et al.2023 · 194 citations
3. A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and RecommendationsConference on Empirical Methods in Natural Language Processing (EMNLP)Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.2024 · 105 citations
4. ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world ScenariosInternational Conference on Computational Linguistics (COLING)Junjie Ye, Guanyu Li, SongYang Gao, et al.2025 · 35 citations
5. Evaluating Language Models as Synthetic Data GeneratorsAnnual Meeting of the Association for Computational Linguistics (ACL)Seungone Kim, Juyoung Suk, Xiang Yue, et al.2025 · 32 citations
6. Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the AboveAnnual Meeting of the Association for Computational Linguistics (ACL)Nishant Balepur, Rachel Rudinger, Jordan Boyd-Graber2025 · 28 citations
7. MedArabiQ: Benchmarking Large Language Models on Arabic Medical TasksarXiv:2505.03427Mouath Abu Daoud, Chaimae Abouzahir, Leen Kharouf, et al.2025 · 22 citations
8. A Survey of Post-Training Scaling in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Hanyu Lai, Xiao Liu, Junjie Gao, et al.2025 · 18 citations
9. MultiPragEval: Multilingual Pragmatic Evaluation of Large Language ModelsProceedings of the 2nd GenBench Workshop on Generalisation (Benchmarking) in NLPDojun Park, Jiwoo Lee, Seohyun Park, et al.2024 · 17 citations
10. ToolHop: A Query-Driven Benchmark for Evaluating Large Language Models in Multi-Hop Tool UseAnnual Meeting of the Association for Computational Linguistics (ACL)Junjie Ye, Zhengyin Du, Xuesong Yao, et al.2025 · 15 citations
11. LLMs Are Biased Towards Output Formats! Systematically Evaluating and Mitigating Output Format Bias of LLMsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Do Xuan Long, Hai Nguyen Ngoc, Tiviatis Sim, et al.2025 · 14 citations
12. Can LLMs assist with Ambiguity? A Quantitative Evaluation of various Large Language Models on Word Sense DisambiguationarXiv:2411.18337T.G.D.K. Sumanathilaka, Nicholas Micallef, Julian Hough2024 · 11 citations
13. Pragmatic Competence Evaluation of Large Language Models for the Korean LanguagePacific Asia Conference on Language, Information and Computation (PACLIC)Dojun Park, Jiwoo Lee, Hyeyun Jeong, et al.2024 · 11 citations
14. Pragmatics beyond humans: meaning, communication, and LLMsarXiv:2508.06167Vit Gvoždiak2025 · 2 citations
15. Beyond Value Benchmarks: Measuring Value-Structure Alignment in Large Language Models via Symmetric Q-SortsAnnual Meeting of the Association for Computational Linguistics (ACL)Jingting Zheng, Yuqi Ren, Linhao Yu, et al.2026 · 1 citation
16. From Curated Data to Scalable Models: Continual Pre-training of Dense and MoE Large Language Models for TibetanAnnual Meeting of the Association for Computational Linguistics (ACL)Lei Yang, Leiyu Pan, Bojian Xiong, et al.2026 · 1 citation
17. AI Safety Lost in Translation: Evaluating the Effectiveness of English-Italian Cross-Lingual LLM Safety AlignmentLanguage Resources and Evaluation Conference (LREC)Alessio Wu, Martim Brandao2026
18. Charting the European LLM Benchmarking Landscape: A New Taxonomy and RegistryShaping Multilingual, Multimodal AI for the Social Sciences and Humanities @ LRECSpela Vintar, Mojca Brglez, Taja Kuzman Pungeršek, et al.2026
19. MASS: Deep Research for Social Sciences with Memory-Augmented Social SimulationFindings of the Association for Computational LinguisticsYongrui Liu, Deyi Xiong2026
20. Neuronal Insights into LLM Attacks: Targeted Neuron Tuning for Precise and Robust Vulnerability PatchingFindings of the Association for Computational LinguisticsDan Shi, Renren Jin, Zhuowen Han, et al.2026
21. The Validity of Coreference-based Evaluations of Natural Language UnderstandingarXiv:2602.16200Ian Porada2026
22. Why Does Reinforcement Learning Generalize? A Feature-Level Mechanistic Study of Post-Training in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Dan Shi, Zhuowen Han, Simon Ostermann, et al.2026

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