5 papers
Explore with Memory, Learn without It: In-Context Exploration and Self-Distillation for LLM Reasoning
Yutong Chen, Zhichao Xu, Rui Liu +1
Exploration bounds learning efficiency in reinforcement learning with verifiable rewards (RLVR). Current methods explore mostly through independent sampling, without fully using th…
More Reasoning Is Not Always Better: Executing Clinical Guidelines with LLMs and Rules
Xiaoqian Lu, Guangfu Guo, Long Cheng +1
Large language models (LLMs) have shown considerable promise in clinical decision support. However, existing approaches often rely on multi-step reasoning or multi-agent collaborat…
Efficient Geothermal Well-Control Optimization via Diffusion-Surrogate Reinforcement Learning
Ruimin Dai, Guodong Chen, Randy Harsuko +2
Real-time decision-making for enhanced geothermal systems (EGS) is challenging because long-term production periods involve high-dimensional control spaces and a large number of ti…
DualOPSD: Closing the Feedback Loop in On-Policy Self-Distillation
Yutong Chen, Guangfu Guo, Zhichao Xu +1
On-policy self-distillation (OPSD) combines student generated trajectories with dense supervision from a privileged teacher of the same model. Its pointwise clipping protects the s…
DeltaFlow: Noise-Adaptive Bidirectional Gated Delta Networks for Embedded Language Flows
Guangfu Guo, Xiaoqian Lu, Linsey Pang +4
Embedded Language Flows (ELF) rely primarily on full non-causal attention for iterative denoising, repeatedly incurring quadratic sequence-mixing cost at each sampling step. Gated…