activity
20242026
collaborators

9 papers

cs.AI2026

Evaluating Counterfactual Sensitivity to Patient Information in Medication-Safety Reasoning

Zhitian Hou, Yuhang Liu, Pengkai Wang +8

Applying a valid medication-safety rule when its patient-specific conditions are not met can produce an incorrect decision. Existing medical evaluations largely use isolated and fi…

cs.CL2026

Beyond Captions: Context-Grounded Reconstruction for Biomedical Multimodal Continued Pretraining

Guanghao Zhu, Zeyu Liu, Zhitian Hou +10

Biomedical figures are explained not by captions alone but by body-text passages that discuss them. Yet current multimodal corpora typically reduce figures to isolated image-captio…

cs.CL2026

InfiMed-ORBIT: Aligning LLMs on Open-Ended Complex Tasks via Rubric-Based Incremental Training

Pengkai Wang, Pengwei Liu, Qi Zuo +3

Reinforcement learning (RL) has powered many recent breakthroughs in large language models (LLMs), especially for tasks where rewards can be computed automatically, such as code ge…

cs.CL2025

InfiMed: Low-Resource Medical MLLMs with Advancing Understanding and Reasoning

Zeyu Liu, Zhitian Hou, Guanghao Zhu +3

Multimodal Large Language Models (MLLMs) have achieved remarkable progress in domains such as visual understanding and mathematical reasoning. However, their application in the med…

cs.AI2025

InfiMed-Foundation: Pioneering Advanced Multimodal Medical Models with Compute-Efficient Pre-Training and Multi-Stage Fine-Tuning

Guanghao Zhu, Zhitian Hou, Zeyu Liu +3

Multimodal large language models (MLLMs) have shown remarkable potential in various domains, yet their application in the medical field is hindered by several challenges. General-p…

cs.AI2025

InfiAlign: A Scalable and Sample-Efficient Framework for Aligning LLMs to Enhance Reasoning Capabilities

Shuo Cai, Su Lu, Qi Zhou +4

Large language models (LLMs) have exhibited impressive reasoning abilities on a wide range of complex tasks. However, enhancing these capabilities through post-training remains res…