14 citations · 15 across the 4 of their papers we have counts for
4 papers
Hybrid supervised instance segmentation by learning label noise suppression
Linwei Chen, Ying Fu, Shaodi You +1
To reach top accuracy, current fully supervised instance segmentation methods severely rely on large-scale pixel-wise labeled datasets. They are usually expensive and time-consumin…
Bringing Value Models Back: Generative Critics for Value Modeling in LLM Reinforcement Learning
Zikang Shan, Han Zhong, Liwei Wang +1
Credit assignment is a central challenge in reinforcement learning (RL). Classical actor-critic methods address this challenge through fine-grained advantage estimation based on a…
DPO Meets PPO: Reinforced Token Optimization for RLHF
Han Zhong, Zikang Shan, Guhao Feng +6
In the classical Reinforcement Learning from Human Feedback (RLHF) framework, Proximal Policy Optimization (PPO) is employed to learn from sparse, sentence-level rewards -- a chall…
Rethinking Model-based, Policy-based, and Value-based Reinforcement Learning via the Lens of Representation Complexity
Guhao Feng, Han Zhong
Reinforcement Learning (RL) encompasses diverse paradigms, including model-based RL, policy-based RL, and value-based RL, each tailored to approximate the model, optimal policy, an…