🔗 Who cites «Benchmark Self-Evolving: A Multi-Agent Framework for Dynamic LLM Evaluation»

28 papers of our library cite it (of the 149,439 whose bibliographies we read) · 6 with a page here, the most cited first · ← back to «Benchmark Self-Evolving: A Multi-Agent Framework for Dynamic LLM Evaluation»

1. 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
2. A Survey on Efficient Large Language Model Training: From Data-centric PerspectivesAnnual Meeting of the Association for Computational Linguistics (ACL)Junyu Luo, Bohan Wu, Xiao Luo, et al.2025 · 14 citations
3. EducationQ: Evaluating LLMs' Teaching Capabilities Through Multi-Agent Dialogue FrameworkAnnual Meeting of the Association for Computational Linguistics (ACL)Yao Shi, Rongkeng Liang, Yong Xu2025 · 14 citations
4. CRITICTOOL: Evaluating Self-Critique Capabilities of Large Language Models in Tool-Calling Error ScenariosConference on Empirical Methods in Natural Language Processing (EMNLP)Shiting Huang, Zhen Fang, Zehui Chen, et al.2025 · 12 citations
5. REST: Stress Testing Large Reasoning Models by Asking Multiple Problems at OnceAnnual Meeting of the Association for Computational Linguistics (ACL)Zhuoshi Pan, Qizhi Pei, Yu Li, et al.2026 · 3 citations
6. Are LLM Benchmarks Already Contaminated? A Systematic Review of Contamination Detection MethodsWorkshop on Generation, Evaluation and Metrics (GEM)Erfan Nourbakhsh, Mohammad Sadegh Sirjani, Amir Mousavi, et al.2026

22 more papers of our library cite it; they have no page here yet.

This page in Markdown → https://md.research.elamur.ai/free/en/papers/wang-2025-benchmark-self-evolving-multi-agent/cited-by/