3 citations · 4 across the 4 of their papers we have counts for
5 papers
Benchmarking Multi-turn Medical Diagnosis: Hold, Lure, and Self-Correction
Jinrui Fang, Runhan Chen, Xu Yang +9
Large language models (LLMs) achieve high accuracy in medical diagnosis when all clinical information is provided in a single turn, yet how they behave under multi-turn evidence ac…
Scaling Medical Reasoning Verification via Tool-Integrated Reinforcement Learning
Hang Zhang, Ruheng Wang, Yuelyu Ji +7
Large language models have achieved strong performance on medical reasoning benchmarks, yet their deployment in clinical settings demands rigorous verification to ensure factual ac…
On the Use of Weighting for Personalized and Transparent Evidence Synthesis
Wenqi Shi, José R. Zubizarreta
Over the past few decades, statistical methods for causal inference have made impressive strides, enabling progress across a range of scientific fields. However, much of this metho…
AI Scientists for Building Virtual-Cell Models
Xiangru Tang, Zhuoyun Yu, Jiapeng Chen +12
Autonomous agents, from virtual laboratories to biological data-analysis agents and co-scientists, have begun to turn scientific goals into hypotheses. Whether they can go further…
MedicalAgentsBench for Complex Medical Reasoning: Comparing Internalized Reasoning Models versus Externalized Agent-based Frameworks
Yanjun Shao, Xiangru Tang, Jiwoong Sohn +10
Complex medical reasoning requires integrating heterogeneous clinical evidence across multiple inference steps. Large language models (LLMs) now approach this through two routes: i…