Summary of Cross-domain Policy Adaptation by Capturing Representation Mismatch, By Jiafei Lyu et al.
Cross-Domain Policy Adaptation by Capturing Representation Mismatchby Jiafei Lyu, Chenjia Bai, Jingwen Yang, Zongqing Lu,…
Summary of Efficient Recurrent Off-policy Rl Requires a Context-encoder-specific Learning Rate, by Fan-ming Luo et al.
Efficient Recurrent Off-Policy RL Requires a Context-Encoder-Specific Learning Rateby Fan-Ming Luo, Zuolin Tu, Zefang Huang,…
Summary of Ivideogpt: Interactive Videogpts Are Scalable World Models, by Jialong Wu et al.
iVideoGPT: Interactive VideoGPTs are Scalable World Modelsby Jialong Wu, Shaofeng Yin, Ningya Feng, Xu He,…
Summary of Cooperative Backdoor Attack in Decentralized Reinforcement Learning with Theoretical Guarantee, by Mengtong Gao et al.
Cooperative Backdoor Attack in Decentralized Reinforcement Learning with Theoretical Guaranteeby Mengtong Gao, Yifei Zou, Zuyuan…
Summary of Intelligent Go-explore: Standing on the Shoulders Of Giant Foundation Models, by Cong Lu et al.
Intelligent Go-Explore: Standing on the Shoulders of Giant Foundation Modelsby Cong Lu, Shengran Hu, Jeff…
Summary of Diffusion Actor-critic with Entropy Regulator, by Yinuo Wang et al.
Diffusion Actor-Critic with Entropy Regulatorby Yinuo Wang, Likun Wang, Yuxuan Jiang, Wenjun Zou, Tong Liu,…
Summary of Extracting Heuristics From Large Language Models For Reward Shaping in Reinforcement Learning, by Siddhant Bhambri et al.
Extracting Heuristics from Large Language Models for Reward Shaping in Reinforcement Learningby Siddhant Bhambri, Amrita…
Summary of Reinforcement Learning For Infinite-horizon Average-reward Linear Mdps Via Approximation by Discounted-reward Mdps, By Kihyuk Hong et al.
Reinforcement Learning for Infinite-Horizon Average-Reward Linear MDPs via Approximation by Discounted-Reward MDPsby Kihyuk Hong, Woojin…
Summary of Mallowspo: Fine-tune Your Llm with Preference Dispersions, by Haoxian Chen et al.
MallowsPO: Fine-Tune Your LLM with Preference Dispersionsby Haoxian Chen, Hanyang Zhao, Henry Lam, David Yao,…
Summary of Interpretable and Editable Programmatic Tree Policies For Reinforcement Learning, by Hector Kohler et al.
Interpretable and Editable Programmatic Tree Policies for Reinforcement Learningby Hector Kohler, Quentin Delfosse, Riad Akrour,…