7 citations · 18 across the 23 of their papers we have counts for
7 papers · 1 filter
GuideSkill: Evolving Executable LLM Agent Skills for Guideline-Grounded Clinical Reasoning
Lang Cao, Yuhao Shen, Tianyang Luo +3
Clinical practice guidelines (CPGs) encode diagnostic criteria, but LLM systems typically retrieve guideline text or absorb it through training rather than execute its rules. We in…
Z-1: Efficient Reinforcement Learning for Vision-Language-Action Models
Lang Cao, Renhong Chen, Luyi Li +3
Vision-Language-Action (VLA) models offer a promising framework for robotic manipulation by connecting language instructions, visual observations, and continuous control. However,…
MedGuideX: Internalizing Decision Logic from Executable Guidelines into Large Language Models for Clinical Reasoning
Yuhao Shen, Lang Cao, Simo Du +4
Clinical practice guidelines (CPGs) encode evidence-based decision logic that clinicians apply by evaluating patient variables, conditional criteria, and recommendation rules. Howe…
RAG or Learning? Understanding the Limits of LLM Adaptation under Continuous Knowledge Drift in the Real World
Hanbing Liu, Lang Cao, Yang Li
Large language models (LLMs) acquire most of their knowledge during pretraining, which ties them to a fixed snapshot of the world and makes adaptation to continuously evolving know…
SupChain-Bench: Benchmarking Large Language Models for Real-World Supply Chain Management
Shengyue Guan, Yihao Liu, Lang Cao
Large language models (LLMs) have shown promise in complex reasoning and tool-based decision making, motivating their application to real-world supply chain management. However, su…
EHR-RAG: Bridging Long-Horizon Structured Electronic Health Records and Large Language Models via Enhanced Retrieval-Augmented Generation
Lang Cao, Qingyu Chen, Yue Guo
Electronic Health Records (EHRs) provide rich longitudinal clinical evidence that is central to medical decision-making, motivating the use of retrieval-augmented generation (RAG)…
TreeAdv: Tree-Structured Advantage Redistribution for Group-Based RL
Lang Cao, Hui Ruan, Yongqian Li +5
Reinforcement learning with group-based objectives, such as Group Relative Policy Optimization (GRPO), is a common framework for aligning large language models on complex reasoning…