--- title: "Who cites An Open Source Data — 47 citing papers" description: "47 papers of the Elamur Research library cite «An Open Source Data Contamination Report for Large Language Models», found in their…" canonical: "https://research.elamur.ai/free/en/papers/li-2023-open-source-data-contamination-report/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/li-2023-open-source-data-contamination-report/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [An Open Source Data Contamination Report for…](https://md.research.elamur.ai/free/en/papers/li-2023-open-source-data-contamination-report/) / cited by # Who cites «An Open Source Data Contamination Report for Large Language Models» 47 papers of our library cite it (of the 149,439 whose bibliographies we read) · 12 with a page here, the most cited first · [← back to «An Open Source Data Contamination Report for Large Language Models»](https://md.research.elamur.ai/free/en/papers/li-2023-open-source-data-contamination-report/) 1. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/) 2. [**Benchmark Data Contamination of Large Language Models: A Survey arXiv:2406.04244**Cheng Xu, Shuhao Guan, Derek Greene, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmark-data-contamination-large/) 3. [**Benchmarking Benchmark Leakage in Large Language Models arXiv:2404.18824**Ruijie Xu, Zengzhi Wang, Run-Ze Fan, et al.*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmarking-benchmark-leakage-large-language/) 4. [**MoRAL: MoE Augmented LoRA for LLMs' Lifelong Learning arXiv:2402.11260**Shu Yang; Muhammad Asif Ali; Cheng-Long Wang; Lijie Hu;, Di Wang*2024 · 21 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-moral-moe-augmented-lora-llms/) 5. **[Auto-Arena: Automating LLM Evaluations with Agent Peer Battles and Committee Discussions](https://md.research.elamur.ai/free/en/papers/zhao-2025-auto-arena-automating-llm-evaluations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruochen Zhao, Wenxuan Zhang, Yew Ken Chia, et al.*2025 · 16 citations* 6. [**PseudoBench: Measuring How Agentic Auto-Research Fuels Pseudoscience arXiv:2606.18060**Xinyang Liao, Lingyu Li, Huacan Liu, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/liao-2026-pseudobench-measuring-agentic-auto/) 7. **[When Do Large Language Models Exhibit Unsolicited Deception?](https://md.research.elamur.ai/free/en/papers/taylor-2026-when-do-large-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Samuel M. Taylor, Benjamin K. Bergen*2026 · 1 citation* 8. **[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* 9. [**Can Large Language Models Reliably Correct Errors in Low-Resource ASR? A Contamination-Aware Case Study on West Frisian arXiv:2605.19711**Yun Hao, Reihaneh Amooie, Wietse de Vries, et al.*2026*](https://md.research.elamur.ai/free/en/papers/hao-2026-large-language-models-reliably-correct/) 10. **[Inflated Excellence or True Performance? Rethinking Medical Diagnostic Benchmarks with Dynamic Evaluation](https://md.research.elamur.ai/free/en/papers/zhang-2026-inflated-excellence-or-true-performance/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangxu Zhang, Lei Li, Yanyun Zhou, et al.*2026* 11. **[Lunar-Bench: Towards Evaluating Task-Oriented Reasoning of LLMs in Lunar Exploration Scenarios](https://md.research.elamur.ai/free/en/papers/xiao-2026-lunar-bench-evaluating-task-oriented/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xin-Yu Xiao, Ye Tian, Erwei Yin, et al.*2026* 12. **[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* 35 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/li-2023-open-source-data-contamination-report/) — An Open Source Data Contamination Report for Large Language Models