3 citations · 3 across the 4 of their papers we have counts for
4 papers
Learning with a Single Rollout via Monte Carlo Pass@k Critic
Fengdi Che, Yang Liu, Lei Yu +4
Estimating token-level advantages in reinforcement learning (RL) for language models remains challenging because scaling up episodic experience collection is expensive. The difficu…
Greed Is Learned: Visible Incentives as Reward-Hacking Triggers
Tong Che, Rui Wu
Deployed agents increasingly act with their reward proxy in view, such as a balance, score, or KPI dashboard. We show that reinforcement learning can make a policy \emph{addicted}…
Constitutional Value Potentials: reading and steering internal priority margins in language models
Tong Che, Rui Wu
A constitution tells a language model what to value, but little tells us whether it does. Adherence is judged from outputs, and output evidence is most fragile on value conflicts,…
LLaMA-Berry: Pairwise Optimization for O1-like Olympiad-Level Mathematical Reasoning
Di Zhang, Jianbo Wu, Jingdi Lei +9
This paper presents an advanced mathematical problem-solving framework, LLaMA-Berry, for enhancing the mathematical reasoning ability of Large Language Models (LLMs). The framework…