4 papers
AtelierEval: Agentic Evaluation of Humans & LLMs as Text-to-Image Prompters
Hanjun Luo, Zhimu Huang, Sylvia Chung +6
Text-to-image (T2I) systems increasingly rely on upstream prompters, either humans or multimodal large language models (MLLMs), to translate user intent into detailed prompts. Yet…
Scaling medical imaging report generation with multimodal reinforcement learning
Qianchu Liu, Sheng Zhang, Guanghui Qin +11
Frontier models have demonstrated remarkable capabilities in understanding and reasoning with natural-language text, but they still exhibit major competency gaps in multimodal unde…
The Illusion of Readiness in Health AI
Yu Gu, Jingjing Fu, Xiaodong Liu +29
Large language models have demonstrated remarkable performance in a wide range of medical benchmarks. Yet underneath the seemingly promising results lie salient growth areas, espec…
X-Reasoner: Towards Generalizable Reasoning Across Modalities and Domains
Qianchu Liu, Sheng Zhang, Guanghui Qin +9
Recent proprietary models (e.g., o3) have begun to demonstrate strong multimodal reasoning capabilities. Yet, most existing open-source research concentrates on training text-only…