--- title: "Who cites Benchmarking Benchmark — 67 citing papers" description: "67 papers of the Elamur Research library cite «Benchmarking Benchmark Leakage in Large Language Models», found in their bibliographies…" canonical: "https://research.elamur.ai/free/en/papers/xu-2024-benchmarking-benchmark-leakage-large-language/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/xu-2024-benchmarking-benchmark-leakage-large-language/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Benchmarking Benchmark Leakage in Large Language…](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmarking-benchmark-leakage-large-language/) / cited by # Who cites «Benchmarking Benchmark Leakage in Large Language Models» 67 papers of our library cite it (of the 149,439 whose bibliographies we read) · 16 with a page here, the most cited first · [← back to «Benchmarking Benchmark Leakage in Large Language Models»](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmarking-benchmark-leakage-large-language/) 1. [**LIMO: Less is More for Reasoning arXiv:2502.03387**Yixin Ye, Zhen Huang, Yang Xiao, et al.*2025 · 209 citations*](https://md.research.elamur.ai/free/en/papers/ye-2025-limo-less-more-reasoning/) 2. [**Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models arXiv:2410.07985**Bofei Gao, Feifan Song, Zhe Yang, et al.*2024 · 163 citations*](https://md.research.elamur.ai/free/en/papers/gao-2024-omni-math-universal-olympiad-level/) 3. **[A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations](https://md.research.elamur.ai/free/en/papers/laskar-2024-systematic-survey-critical-review-evaluating/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.*2024 · 105 citations* 4. **[A Careful Examination of Large Language Model Performance on Grade School Arithmetic](https://md.research.elamur.ai/free/en/papers/zhang-2024-careful-examination-large-language-model/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hugh Zhang, Jeff Da, Dean Lee, et al.*2024 · 101 citations* 5. [**BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval arXiv:2407.12883**Hongjin Su, Howard Yen, Mengzhou Xia, et al.*2024 · 77 citations*](https://md.research.elamur.ai/free/en/papers/su-2024-bright-realistic-challenging-benchmark-reasoning/) 6. [**MedXpertQA: Benchmarking Expert-Level Medical Reasoning and Understanding arXiv:2501.18362**Yuxin Zuo, Shang Qu, Yifei Li, et al.*2025 · 65 citations*](https://md.research.elamur.ai/free/en/papers/zuo-2025-medxpertqa-benchmarking-expert-level-medical/) 7. **[OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI](https://md.research.elamur.ai/free/en/papers/huang-2024-olympicarena-benchmarking-multi-discipline-cognitive/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhen Huang, Zengzhi Wang, Shijie Xia, et al.*2024 · 56 citations* 8. [**Beyond Accuracy: Evaluating the Reasoning Behavior of Large Language Models — A Survey arXiv:2404.01869**Philipp Mondorf, Barbara Plank*2024 · 53 citations*](https://md.research.elamur.ai/free/en/papers/mondorf-2024-accuracy-evaluating-reasoning-behavior-large/) 9. **[On Memorization of Large Language Models in Logical Reasoning](https://md.research.elamur.ai/free/en/papers/xie-2025-memorization-large-language-models-logical/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Chulin Xie, Yangsibo Huang, Chiyuan Zhang, et al.*2025 · 45 citations* 10. **[BIG5-CHAT: Shaping LLM Personalities Through Training on Human-Grounded Data](https://md.research.elamur.ai/free/en/papers/li-2025-big5-chat-shaping-llm-personalities/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenkai Li, Jiarui Liu, Andy Liu, et al.*2025 · 42 citations* 11. **[Challenging the Boundaries of Reasoning: An Olympiad-Level Math Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/sun-2026-challenging-boundaries-reasoning-olympiad-level/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoxiang Sun, Yingqian Min, Zhipeng Chen, et al.*2026 · 25 citations* 12. [**JustLogic: A Comprehensive Benchmark for Evaluating Deductive Reasoning in Large Language Models arXiv:2501.14851**Michael K. Chen, Xikun Zhang, Dacheng Tao*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-justlogic-comprehensive-benchmark-evaluating-deductive/) 13. **[LLMEval-Fair: A Large-Scale Longitudinal Study on Robust and Fair Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-llmeval-fair-large-scale-longitudinal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ming Zhang, Yujiong Shen, Jingyi Deng, et al.*2026 · 3 citations* 14. **[Are LLM Benchmarks Already Contaminated? A Systematic Review of Contamination Detection Methods](https://md.research.elamur.ai/free/en/papers/nourbakhsh-2026-are-llm-benchmarks-already-contaminated/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Erfan Nourbakhsh, Mohammad Sadegh Sirjani, Amir Mousavi, et al.*2026* 15. **[Benchmark Data Contamination in Underrepresented Languages: A Comprehensive Analysis Using Brazilian Data](https://md.research.elamur.ai/free/en/papers/vilar-2026-benchmark-data-contamination-underrepresented-languages/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Iriedson Souto Maior de Moraes Vilar, David Candeia Maia, João Brunet, et al.*2026* 16. **[SPENCE: A Syntactic Probe for Detecting Contamination in NL2SQL Benchmarks](https://md.research.elamur.ai/free/en/papers/safarzadeh-2026-spence-syntactic-probe-detecting-contamination/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohammadtaher Safarzadeh, Hitesh Laxmichand Patel, Afshin Oroojlooy, et al.*2026* 51 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmarking-benchmark-leakage-large-language/) — Benchmarking Benchmark Leakage in Large Language Models