38 citations · 69 across the 28 of their papers we have counts for
5 papers · 1 filter
AutoSearch: Adaptive Search Depth for Efficient Agentic RAG via Reinforcement Learning
Jingbo Sun, Wenyue Chong, Songjun Tu +7
Agentic retrieval-augmented generation (RAG) systems enable large language models (LLMs) to solve complex tasks through multi-step interaction with external retrieval tools. Howeve…
Dynamic Dual-Granularity Skill Bank for Agentic RL
Songjun Tu, Chengdong Xu, Qichao Zhang +5
Agentic RL can benefit substantially from reusable experience, yet existing skill-based methods mainly extract trajectory-level guidance and often lack principled mechanisms for ma…
Salience-Invariant Consistent Policy Learning for Generalization in Visual Reinforcement Learning
Jingbo Sun, Songjun Tu, Qichao Zhang +2
Generalizing policies to unseen scenarios remains a critical challenge in visual reinforcement learning, where agents often overfit to the specific visual observations of the train…
In-Dataset Trajectory Return Regularization for Offline Preference-based Reinforcement Learning
Songjun Tu, Jingbo Sun, Qichao Zhang +4
Offline preference-based reinforcement learning (PbRL) typically operates in two phases: first, use human preferences to learn a reward model and annotate rewards for a reward-free…
A Reinforcement Learning Benchmark for Autonomous Driving in Intersection Scenarios
Yuqi Liu, Qichao Zhang, Dongbin Zhao
In recent years, control under urban intersection scenarios becomes an emerging research topic. In such scenarios, the autonomous vehicle confronts complicated situations since it…