🔗 Who cites «Don't Make Your LLM an Evaluation Benchmark Cheater»

95 papers of our library cite it (of the 149,439 whose bibliographies we read) · 25 with a page here, the most cited first · ← back to «Don't Make Your LLM an Evaluation Benchmark Cheater»

1. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
2. LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for CodearXiv:2403.07974Naman Jain, King Han, Alex Gu, et al.2024 · 578 citations
3. Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMsConference on Neural Information Processing Systems (NeurIPS)Shengbang Tong, Ellis Brown, Penghao Wu, et al.2024 · 208 citations
4. Investigating Data Contamination in Modern Benchmarks for Large Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Chunyuan Deng, Yilun Zhao, Xiangru Tang, et al.2024 · 137 citations
5. 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
6. Task Contamination: Language Models May Not Be Few-Shot AnymoreProceedings of the AAAI Conference on Artificial IntelligenceChangmao Li, Jeffrey Flanigan2023 · 89 citations
7. Benchmark Data Contamination of Large Language Models: A SurveyarXiv:2406.04244Cheng Xu, Shuhao Guan, Derek Greene, et al.2024 · 85 citations
8. BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive RetrievalarXiv:2407.12883Hongjin Su, Howard Yen, Mengzhou Xia, et al.2024 · 77 citations
9. SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-ScalingarXiv:2312.15166Dahyun Kim, Chanjun Park, Sanghoon Kim, et al.2023 · 77 citations
10. Benchmarking Benchmark Leakage in Large Language ModelsarXiv:2404.18824Ruijie Xu, Zengzhi Wang, Run-Ze Fan, et al.2024 · 73 citations
11. AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination EvaluationarXiv:2311.07397Junyang Wang, Yuhang Wang, Guohai Xu, et al.2023 · 67 citations
12. A Peek into Token Bias: Large Language Models Are Not Yet Genuine ReasonersConference on Empirical Methods in Natural Language Processing (EMNLP)Bowen Jiang, Yangxinyu Xie, Zhuoqun Hao, et al.2024 · 64 citations
13. Artifacts or Abduction: How Do LLMs Answer Multiple-Choice Questions Without the Question?Annual Meeting of the Association for Computational Linguistics (ACL)Nishant Balepur, Abhilasha Ravichander, Rachel Rudinger2024 · 52 citations
14. LV-Eval: A Balanced Long-Context Benchmark with 5 Length Levels Up to 256KarXiv:2402.05136Tao Yuan, Xuefei Ning, Dong Zhou, et al.2024 · 41 citations
15. Benchmark Self-Evolving: A Multi-Agent Framework for Dynamic LLM EvaluationInternational Conference on Computational Linguistics (COLING)Siyuan Wang, Zhuohan Long, Zhihao Fan, et al.2025 · 30 citations
16. 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
17. Large Language Models as Biomedical Hypothesis Generators: A Comprehensive EvaluationarXiv:2407.08940Biqing Qi, Kaiyan Zhang, Kai Tian, et al.2024 · 19 citations
18. DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning GraphConference on Neural Information Processing Systems (NeurIPS)Zhehao Zhang, Jiaao Chen, Diyi Yang2024 · 17 citations
19. WorldSense: A Synthetic Benchmark for Grounded Reasoning in Large Language ModelsarXiv:2311.15930Youssef Benchekroun, Megi Dervishi, Mark Ibrahim, et al.2023 · 15 citations
20. Beyond Math: Stories as a Testbed for Memorization-Constrained Reasoning in LLMsConference of the European Chapter of the Association for Computational Linguistics (EACL)Yuxuan Jiang, Francis Ferraro2026 · 10 citations
21. How Quantization Shapes Bias in Large Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Federico Marcuzzi, Xuefei Ning, Roy Schwartz, et al.2026 · 3 citations
22. When Flores Bloomz Wrong: Cross-Direction Contamination in Machine Translation EvaluationConference of the European Chapter of the Association for Computational Linguistics (EACL)David Tan, Pinzhen Chen, Josef van Genabith, et al.2026 · 2 citations
23. GAOKAO-Eval: Does high scores truly reflect strong capabilities in LLMs?arXiv:2412.10056Zhikai Lei, Tianyi Liang, Hanglei Hu, et al.2024 · 1 citation
24. BenchNavigator: A Discovery Interface for Comparing LLM BenchmarksWorkshop on Evaluating Evaluations (EvalEval)Anna Sokol, Inge Vejsbjerg, Elizabeth M. Daly, et al.2026
25. 360Zhinao Technical ReportarXiv:2405.133862024

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