🔗 Who cites «Feedback Loops With Language Models Drive In-Context Reward Hacking»

24 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 «Feedback Loops With Language Models Drive In-Context Reward Hacking»

1. The WMDP Benchmark: Measuring and Reducing Malicious Use With UnlearningarXiv:2403.03218Nathaniel Li, Alexander Pan, Anjali Gopal, et al.2024 · 127 citations
2. Quiet-STaR: Language models can teach themselves to think before speaking2024 · 122 citations
3. Thinking beyond the anthropomorphic paradigm benefits LLM researchAnnual Meeting of the Association for Computational Linguistics (ACL)Lujain Ibrahim, Myra Cheng2026 · 8 citations
4. Workflow Closure Is Not Scientific Closure in Auto-Research SystemsarXiv:2605.26200Shuai Wang, Xinyuan Tian, Pangpang Liu, et al.2026 · 1 citation
5. Alignment Tuning for Large Language Models: A Data-Centric Lens on Alignment Data PipelinesFindings of the Association for Computational LinguisticsHwanjun Song2026
6. Curing Miracle Steps in LLM Mathematical Reasoning with Rubric RewardsAnnual Meeting of the Association for Computational Linguistics (ACL)Youliang Yuan, Qiuyang Mang, Jingbang Chen, et al.2026
7. LCO: LLM-based Constraint Optimization for Safer Agentic LLMs in Real-world TasksFindings of the Association for Computational LinguisticsJiayong Wan, Jiawei Chen, Zhaoxia Yin, et al.2026

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

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