🔗 Who cites «LLM-as-a-Judge & Reward Model: What They Can and Cannot Do»

26 papers of our library cite it (of the 149,439 whose bibliographies we read) · 4 with a page here, the most cited first · ← back to «LLM-as-a-Judge & Reward Model: What They Can and Cannot Do»

1. DARS: Dynamic Action Re-Sampling to Enhance Coding Agent Performance by Adaptive Tree TraversalAnnual Meeting of the Association for Computational Linguistics (ACL)Vaibhav Aggarwal, Ojasv Kamal, Abhinav Japesh, et al.2025 · 4 citations
2. SCAN: Structured Capability Assessment and Navigation for LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Zongqi Wang, Tianle Gu, Chen Gong, et al.2026 · 1 citation
3. Analysing Differences in Persuasive Language in LLM-Generated Text: Uncovering Stereotypical Gender PatternsFindings of the Association for Computational LinguisticsAmalie Brogaard Pauli, Maria Barrett, Max Müller-Eberstein, et al.2026
4. From Conversation to Evaluation: Benchmarking LLMs on Development Knowledge via SimpleDevQAFindings of the Association for Computational LinguisticsJing Zhang, Lianghong Guo, Yanlin Wang, 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/son-2024-llm-judge-reward-model-they/cited-by/