4 papers
The Thinking Leakage in Reinforcement Learning for LLMs
Wenxuan Zhu, Shuming Liu, Bang An +4
Hybrid reasoning models such as the Qwen3 series switch between a THINK mode and a NO-THINK mode through a few chat-template tokens. A popular recipe trains such models with reinfo…
Training-Free Inference-Time Self-Reflection and Cost-Bounded Early Stopping for Large Language Models
Wei Yu, Suxing Liu, Minjie Yu +4
Reinforcement-learning training of reasoning LLMs (e.g., GRPO) is expensive and requires a controllable environment, committing every contribution to a full training pipeline. We p…
Traceable Fault Diagnosis for Battery Energy Storage Systems via Retrieval-Augmented Multi-Agent O&M Assistant
Jiangdi Ru, Bing Li, Yage Huang +2
Large-scale battery energy storage systems (BESSs) require O&M decisions that combine alarms, cell-level measurements, device topology, diagnostic tables, historical cases, and mai…
MetaResearcher: Scaling Deep Research via Self-Reflective Reinforcement Learning in Adversarial Virtual Environments
Wei Yu, Suxing Liu, Minjie Yu +4
Deep research agents have demonstrated remarkable capabilities in autonomous information gathering and synthesis, yet their training remains constrained by the static nature of sim…