4 citations · 8 across the 26 of their papers we have counts for
9 papers · 1 filter
GenPO++: Generative Policy Optimization with Jacobian-free Likelihood Ratios
Ke Hu, Shutong Ding, Panxin Tao +2
Generative policies provide expressive and multimodal action distributions, making them attractive for reinforcement learning (RL) in complex continuous-control tasks. Among them,…
Conformal Reliability: A New Evaluation Metric for Conditional Generation
Yachen Gao, Xinwei Sun, Yikai Wang +4
Conditional generative models have recently achieved remarkable success in various applications. However, a suitable metric for evaluating the reliability of these models, which ta…
GenPO: Generative Diffusion Models Meet On-Policy Reinforcement Learning
Shutong Ding, Ke Hu, Shan Zhong +5
Recent advances in reinforcement learning (RL) have demonstrated the powerful exploration capabilities and multimodality of generative diffusion-based policies. While substantial p…
Diffusion-based Reinforcement Learning via Q-weighted Variational Policy Optimization
Shutong Ding, Ke Hu, Zhenhao Zhang +5
Diffusion models have garnered widespread attention in Reinforcement Learning (RL) for their powerful expressiveness and multimodality. It has been verified that utilizing diffusio…
Harmonizing Generalization and Personalization in Federated Prompt Learning
Tianyu Cui, Hongxia Li, Jingya Wang +1
Federated Prompt Learning (FPL) incorporates large pre-trained Vision-Language models (VLM) into federated learning through prompt tuning. The transferable representations and rema…
Global and Local Prompts Cooperation via Optimal Transport for Federated Learning
Hongxia Li, Wei Huang, Jingya Wang +1
Prompt learning in pretrained visual-language models has shown remarkable flexibility across various downstream tasks. Leveraging its inherent lightweight nature, recent research a…