MedCLM: Learning to Localize and Reason via a CoT-Curriculum in Medical Vision-Language Models
A.I.MATICS Inc（A.I.MATICS公司）；Boston University（波士顿大学）；University of Southern California（南加州大学）；Heuron（Heuron公司）；MODULABS, Open Neural Networks Research Lab（MODULABS，开放神经网络研究实验室）
Soo Yong Kim, Suin Cho, Vincent-Daniel Yun, Gyeongyeon Hwang
Bridging clinical diagnostic reasoning with AI remains a central challenge in medical imaging. We introduce MedCLM, an automated pipeline that converts detection datasets into large-scale medical visual question answering (VQA) data with Chain-of-Thought (CoT) reasoning by linking lesion boxes to organ segmentation and structured rationales. These contextual signals enable medical vision-language models to generate question-answer pairs with step-by-step reasoning. To utilize this data effectively, we propose an Integrated CoT-Curriculum Strategy composed of an Easy stage with explicit lesion boxes for visual grounding, a Medium stage that encourages implicit localization, and a Hard stage for weakly supervised reasoning. Experimental results demonstrate that MedCLM attains state-of-the-art performance on several medical VQA benchmarks, providing a scalable framework for developing clinically aligned medical vision-language models.
From Atoms to Chains: Divergence-Guided Reasoning Curriculum for Unlabeled LLM Domain Adaptation
Beijing Key Laboratory of Intelligent Information Technology, School of Computer Science and Technology, Beijing Institute of Technology（北京智能信息科技重点实验室，计算机科学与技术学院，北京理工大学）；ByteDance China（字节跳动中国）
From Perception to Planning: Evolving Ego-Centric Task-Oriented Spatiotemporal Reasoning via Curriculum Learning
Zhejiang University（浙江大学）；Tianjin University（天津大学）；Qingdao University（青岛大学）；Shanghai Jiao Tong University（上海交通大学）；National University of Singapore（新加坡国立大学）
COTCAgent: Preventive Consultation via Probabilistic Chain-of-Thought Completion
School of Computing and Data Science, The University of Hong Kong（香港大学计算与数据科学学院）；Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China（中国电子科学与技术大学深圳高级研究所）；School of Computer Science, The University of Sydney（悉尼大学计算机科学学院）
V-Retrver: Evidence-Driven Agentic Reasoning for Universal Multimodal Retrieval
Tsinghua University（清华大学）；University of Central Florida（中央佛罗里达大学）；Fudan University（复旦大学）；The Australian National University（澳大利亚国立大学）；The University of Hong Kong（香港大学）；Pengcheng Laboratory（鹏城实验室）；Central South University（中南大学）
EgoThinker: Unveiling Egocentric Reasoning with Spatio-Temporal CoT
Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；Zhejiang University（浙江大学）；The University of Tokyo（东京大学）；Fudan University（复旦大学）；Nanjing University（南京大学）
LLM-Powered Flood Depth Estimation from Social Media Imagery: A Vision-Language Model Framework with Mechanistic Interpretability for Transportation Resilience
Mimicking the Physicist's Eye:A VLM-centric Approach for Physics Formula Discovery
UNC–Chapel Hill（北卡罗来纳大学教堂山分校）；HKUST (Guangzhou)（香港科技大学（广州））；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；Fudan University（复旦大学）；Tsinghua University（清华大学）；Nankai University（南开大学）；UC Santa Cruz（圣塔克鲁兹大学）；The Chinese University of Hong Kong（香港中文大学）；Shanghai Innovation Institute（上海创新研究院）
LlamaV-o1: Rethinking Step-by-step Visual Reasoning in LLMs
Mohamed bin Zayed University of AI（穆罕默德·本·扎耶德人工智能大学）；University of Central Florida（中佛罗里达大学）；Linköping University（林雪平大学）；Australian National University（澳大利亚国立大学）
Visual Enhanced Depth Scaling for Multimodal Latent Reasoning
Beijing Institute of Technology（北京理工大学）；AMAP, Alibaba Group（阿里集团AMAP）；City University of Hong Kong（香港城市大学）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；Yangtze Delta Region Academy of Beijing Institude of Technology, Jiaxing, China（北京理工大学扬子江地区学院，嘉兴，中国）
