1 citations · 1 across the 7 of their papers we have counts for
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Bradley-Terry Policy Optimization for Generative Preference Modeling
Shengyu Feng, Yun He, Shuang Ma +12
Reinforcement learning (RL) has recently proven effective at scaling chain-of-thought (CoT) reasoning in large language models for tasks with verifiable answers. However, extending…
Regularized Langevin Dynamics for Combinatorial Optimization
Shengyu Feng, Yiming Yang
This work proposes a simple yet effective sampling framework for combinatorial optimization (CO). Our method builds on discrete Langevin dynamics (LD), an efficient gradient-guided…
SORREL: Suboptimal-Demonstration-Guided Reinforcement Learning for Learning to Branch
Shengyu Feng, Yiming Yang
Mixed Integer Linear Program (MILP) solvers are mostly built upon a Branch-and-Bound (B\&B) algorithm, where the efficiency of traditional solvers heavily depends on hand-crafted h…
Step-by-Step Reasoning for Math Problems via Twisted Sequential Monte Carlo
Shengyu Feng, Xiang Kong, Shuang Ma +5
Augmenting the multi-step reasoning abilities of Large Language Models (LLMs) has been a persistent challenge. Recently, verification has shown promise in improving solution consis…