🔗 Who cites «Dynamic Evaluation of Large Language Models by Meta Probing Agents»

29 papers of our library cite it (of the 149,439 whose bibliographies we read) · 7 with a page here, the most cited first · ← back to «Dynamic Evaluation of Large Language Models by Meta Probing Agents»

1. 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
2. On the Diversity of Synthetic Data and its Impact on Training Large Language ModelsarXiv:2410.15226Hao Chen, Abdul Waheed, Xiang Li, et al.2024 · 35 citations
3. 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
4. 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
5. TripleFact: Defending Data Contamination in the Evaluation of LLM-driven Fake News DetectionAnnual Meeting of the Association for Computational Linguistics (ACL)Cheng Xu, Nan Yan2025 · 12 citations
6. LLM-Powered Benchmark Factory: Reliable, Generic, and EfficientAnnual Meeting of the Association for Computational Linguistics (ACL)Peiwen Yuan, Shaoxiong Feng, Yiwei Li, et al.2026 · 3 citations
7. 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.

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