Improving Reward Models with Proximal Policy Exploration for Preference-Based Reinforcement Learning
Sep 26, 2025
Key Decision-Makers in Multi-Agent Debates: Who Holds the Power?
Analyzes mediator roles and decisive voices within multi-agent debate frameworks, revealing how influence shifts throughout deliberation.
Feb 15, 2025
SheetAgent: towards a generalist agent for spreadsheet reasoning and manipulation via large language models
SheetAgent, an novel autonomous agent that utilizes the power of LLMs.
Jan 8, 2025
Optimizing Reward Models with Proximal Policy Exploration in Preference-Based Reinforcement Learning
Jul 1, 2024
Ovd-explorer: Optimism should not be the sole pursuit of exploration in noisy environments
We propose Optimistic Value Distribution Explorer (OVD-Explorer) to achieve a noise-aware optimistic exploration for continuous control.
May 1, 2024
A trajectory perspective on the role of data sampling techniques in offline reinforcement learning
Organizing samples in a trajective manner can improve the learning efficiency for offline RL algorithms.
May 1, 2024
vMFER: Von Mises-Fisher experience resampling based on uncertainty of gradient directions for policy improvement
Jan 1, 2024
Uni-RLHF: Universal Platform and Benchmark Suite for Reinforcement Learning with Diverse Human Feedback
Jan 1, 2024
Kisa: A unified keyframe identifier and skill annotator for long-horizon robotics demonstrations
Jan 1, 2024
ENOTO: improving offline-to-online reinforcement learning with Q-ensembles
Jan 1, 2024