20 papers
Learning from Environmental Feedback: Credit Assignment across Multiple Timescales for Agentic Reinforcement Learning
Yifu Huo, Shunjie Xing, Chenglong Wang +8
Agentic reinforcement learning (RL) often suffers from delayed and sparse rewards in real-world environments. A promising solution to this challenge is credit assignment, which aim…
FlowCTS: On-policy Continuous Trajectory Supervision of Flow Models
Kaiyang Ye, Yuan Ge, Junxiang Zhang +8
While on-policy distillation (OPD) effectively addresses sparse rewards and exposure bias in large language model post-training, its extension to flow models remains underexplored.…
ToFu: A White-Box, Token-Efficient Agent Harness for Researchers
Junhao Ruan, Yuan Ge, Bei Li +7
ToFu is an open‑source, white‑box agentic harness that lets researchers automate codebase reading, file editing, command execution, and tool integration with high token efficiency…
HybridThinker: Efficient Chain-of-Thought Reasoning via Compressed Memory and Transient Thought Steps
Xin Liu, Runsong Zhao, Xinyu Liu +8
Extended chain-of-thought (CoT) traces improve LLM reasoning but incur substantial computational and memory costs. While existing CoT compression methods mitigate this by condensin…
Teacher-Guided Policy Optimization for On-Policy Reasoning Distillation under Large Policy Divergence
Xinyu Liu, Kechen Jiao, Chunyang Xiao +10
On-policy distillation (OPD) has become a promising paradigm for reasoning-oriented post-training of large language models (LLMs), especially when combined with reinforcement learn…
StateRAG: Typed State Contracts for Complex Retrieval-Augmented Generation
Miaohe Niu, Pengxiang Li, Lianlei Shan +3
Complex retrieval-augmented generation requires evidence retrieval and control over what to retrieve next, which paths to explore, whether evidence is sufficient, and which interme…