8 citations · 8 across the 2 of their papers we have counts for
2 papers
cs.CL2025
CoLD: Counterfactually-Guided Length Debiasing for Process Reward Models in Mathematical Reasoning
Congmin Zheng, Jiachen Zhu, Jianghao Lin +6
Process Reward Models (PRMs) play a central role in evaluating and guiding multi-step reasoning in large language models (LLMs), especially for mathematical problem solving. Howeve…
cs.SE2024★ 8 cited
LLM Critics Help Catch LLM Bugs
Nat McAleese, Rai Michael Pokorny, Juan Felipe Ceron Uribe +3
Reinforcement learning from human feedback (RLHF) is fundamentally limited by the capacity of humans to correctly evaluate model output. To improve human evaluation ability and ove…