1 citations · 2 across the 9 of their papers we have counts for
6 papers · 1 filter
Self-Evolve With a Reference:Anchored Training of Tool-Integrated Agents
Wenjie Liao, Liangjie Zhao, Zehong Cao
Self-evolving tool-integrated agents learn from tasks and feedback generated within their own training loop. A Curriculum Agent generates tasks, while an Executor Agent learns from…
Can We Trust the Teacher? Decoupled Credit Direction-Magnitude for Self-Distillation
Yugu Li, Zehong Cao, Peizhen Li +3
RLVR provides reliable trajectory-level credit, while OPSD offers dense supervision for token-level credit. This exposes a fundamental coupling when updating step-level credit dire…
UnifiedPlayers: Enhance Tool-Integrated Reasoning in Agentic Reinforcement Learning
Wenjie Liao, Liangjie Zhao, Zehong Cao
Self-evolving methods reduce the need for human-annotated trajectories by allowing tool-using agents to generate their own training data. Yet existing methods typically separate tr…
RTPO: Reverse-Turn Policy Optimization for Stabilizing Agentic RL Training
Yugu Li, Zehong Cao, Jianglin Qiao +1
Training multi-turn agentic workflows with reinforcement learning (RL) enables large language models to perform complex reasoning, use external tools, and conduct iterative search…
KD-MARL: Resource-Aware Knowledge Distillation in Multi-Agent Reinforcement Learning
Monirul Islam Pavel, Siyi Hu, Muhammad Anwar Masum +3
Real world deployment of multi agent reinforcement learning MARL systems is fundamentally constrained by limited compute memory and inference time. While expert policies achieve hi…
Multi-Agent Reinforcement Learning for Heterogeneous Satellite Cluster Resources Optimization
Mohamad A. Hady, Siyi Hu, Mahardhika Pratama +2
This work investigates resource optimization in heterogeneous satellite clusters performing autonomous Earth Observation (EO) missions using Reinforcement Learning (RL). In the pro…