🔗 Who cites «NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity Classes»

35 papers of our library cite it (of the 149,439 whose bibliographies we read) · 5 with a page here, the most cited first · ← back to «NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity Classes»

1. MixEval: Deriving Wisdom of the Crowd from LLM Benchmark MixturesConference on Neural Information Processing Systems (NeurIPS)Jinjie Ni, Fuzhao Xue, Xiang Yue, et al.2024 · 47 citations
2. 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
3. RuleArena: A Benchmark for Rule-Guided Reasoning with LLMs in Real-World ScenariosAnnual Meeting of the Association for Computational Linguistics (ACL)Ruiwen Zhou, Wenyue Hua, Liangming Pan, et al.2025 · 21 citations
4. Human or LLM as Standardized Patients? A Comparative Study in Medical EducationAnnual Meeting of the Association for Computational Linguistics (ACL)Bingquan Zhang, Xiaoxiao Liu, Yuchi Wang, et al.2026 · 1 citation
5. What Makes an LLM a Good Optimizer? A Trajectory Analysis of LLM-Guided Evolutionary SearchFindings of the Association for Computational LinguisticsXinhao Zhang, Xi Chen, François Portet, et al.2026 · 1 citation

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

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