9 citations · 11 across the 8 of their papers we have counts for
9 papers
Distributed Team Orchestration via Supervisor Networks: Convergence, Optimality, and Resilience
Juntian Zhu, Guanpu Chen, Tongtian Zhu +3
In this paper, we study zero-sum potential team games with a supervisor network, where agents rely on supervisor-provided belief information rather than accurate common beliefs. Th…
Nightmare Dreamer: Dreaming About Unsafe States And Planning Ahead
Oluwatosin Oseni, Shengjie Wang, Jun Zhu +1
Reinforcement Learning (RL) has shown remarkable success in real-world applications, particularly in robotics control. However, RL adoption remains limited due to insufficient safe…
DiffusionNFT: Online Diffusion Reinforcement with Forward Process
Kaiwen Zheng, Huayu Chen, Haotian Ye +7
Online reinforcement learning (RL) has been central to post-training language models, but its extension to diffusion models remains challenging due to intractable likelihoods. Rece…
When a Reinforcement Learning Agent Encounters Unknown Unknowns
Juntian Zhu, Miguel de Carvalho, Zhouwang Yang +1
An AI agent might surprisingly find she has reached an unknown state which she has never been aware of -- an unknown unknown. We mathematically ground this scenario in reinforcemen…
A Regularized Newton Method for Nonconvex Optimization with Global and Local Complexity Guarantees
Yuhao Zhou, Jintao Xu, Bingrui Li +3
Finding an -stationary point of a nonconvex function with a Lipschitz continuous Hessian is a central problem in optimization. Regularized Newton methods are a classical tool an…
Aligning Diffusion Behaviors with Q-functions for Efficient Continuous Control
Huayu Chen, Kaiwen Zheng, Hang Su +1
Drawing upon recent advances in language model alignment, we formulate offline Reinforcement Learning as a two-stage optimization problem: First pretraining expressive generative p…
Towards Efficient Exact Optimization of Language Model Alignment
Haozhe Ji, Cheng Lu, Yilin Niu +5
The alignment of language models with human preferences is vital for their application in real-world tasks. The problem is formulated as optimizing the model's policy to maximize t…
DPM-Solver-v3: Improved Diffusion ODE Solver with Empirical Model Statistics
Kaiwen Zheng, Cheng Lu, Jianfei Chen +1
Diffusion probabilistic models (DPMs) have exhibited excellent performance for high-fidelity image generation while suffering from inefficient sampling. Recent works accelerate the…
Score Regularized Policy Optimization through Diffusion Behavior
Huayu Chen, Cheng Lu, Zhengyi Wang +2
Recent developments in offline reinforcement learning have uncovered the immense potential of diffusion modeling, which excels at representing heterogeneous behavior policies. Howe…