15 papers
CoWorld Reasoner: Agentic Multimodal Reasoning with the Evolving Video World Model-Driven Harness
Dongjie Cheng, Ruifeng Yuan, Ran Wei +3
As Vision-Language Models (VLMs) advance, they are increasingly expected to perform spatiotemporal reasoning over motion, actions, and view changes beyond what the input images sho…
Neos: Learning to Interleave Search and Visual Reasoning
Ekko He, Jack Hong, Shilin Yan +8
Recent multimodal deep search agents have advanced tool use and visual content retrieval, yet they still struggle to convert intermediate visual evidence into actionable guidance f…
Evidence-Grounded AI for Musculoskeletal Care
Wenjie Li, Yujie Zhang, Fanrui Zhang +34
Musculoskeletal diseases are among the leading causes of disability and drive the greatest global need for rehabilitation. Because recovery, remodelling and degeneration of bones,…
Experience Makes Skillful: Enabling Generalizable Medical Agent Reasoning via Self-Evolving Skill Memory
Haoran Sun, Wenjie Li, Yujie Zhang +8
Medical agent systems are increasingly expected to support interactive clinical decision making rather than only static question answering. In such settings, effective agents must…
SpatialWorld: Benchmarking Interactive Spatial Reasoning of Multimodal Agents in Real-World Tasks
Hongcheng Gao, Hailong Qu, Jingyi Tang +18
Spatial reasoning is a foundational capability for multimodal large language models (MLLMs) to perceive and operate within the physical world. However, existing benchmarks predomin…
Beyond APIs: Probing the Limits of MLLMs in Physical Tool Use
Zhixin Ma, Yutong Zhou, Yongqi Li +2
Multimodal Large Language Models (MLLMs) excel at utilizing digital APIs and increasingly serve as the "brain" of embodied AI, instructing robots to interact with the physical worl…
Optical Reasoning: Rethinking Images as an Expressive Reasoning Medium Beyond Text
Yutong Bian, Dongjie Cheng, Heming Xia +2
Chain-of-Thought (CoT) improves the performance of Large Language Models (LLMs) and has been extended to Multimodal Large Language Models (MLLMs). More recent work further moves fr…
MedProbeBench: Systematic Benchmarking at Deep Evidence Integration for Expert-level Medical Guideline
Jiyao Liu, Jianghan Shen, Sida Song +19
Recent advances in deep research systems enable large language models to retrieve, synthesize, and reason over large-scale external knowledge. In medicine, developing clinical guid…
Seeing Isn't Believing: Mitigating Belief Inertia via Active Intervention in Embodied Agents
Hanlin Wang, Chak Tou Leong, Jian Wang +1
Recent advancements in large language models (LLMs) have enabled agents to tackle complex embodied tasks through environmental interaction. However, these agents still make subopti…
MedScope: Incentivizing "Think with Videos" for Clinical Reasoning via Coarse-to-Fine Tool Calling
Wenjie Li, Yujie Zhang, Haoran Sun +11
Long-form clinical videos are central to visual evidence-based decision-making, with growing importance for applications such as surgical robotics and related settings. However, cu…
RSAgent: Learning to Reason and Act for Text-Guided Segmentation via Multi-Turn Tool Invocations
Xingqi He, Yujie Zhang, Shuyong Gao +6
Text-guided object segmentation requires both cross-modal reasoning and pixel grounding abilities. Most recent methods treat text-guided segmentation as one-shot grounding, where t…
Code-in-the-Loop Forensics: Agentic Tool Use for Image Forgery Detection
Fanrui Zhang, Qiang Zhang, Sizhuo Zhou +10
Existing image forgery detection (IFD) methods either exploit low-level, semantics-agnostic artifacts or rely on multimodal large language models (MLLMs) with high-level semantic k…
Ophiuchus: Incentivizing Tool-augmented "Think with Images" for Joint Medical Segmentation, Understanding and Reasoning
Yankai Jiang, Yujie Zhang, Peng Zhang +5
Recent medical MLLMs have made significant progress in generating step-by-step textual reasoning chains. However, they still struggle with complex clinical tasks that necessitate d…
CX-Mind: A Pioneering Multimodal Large Language Model for Interleaved Reasoning in Chest X-ray via Curriculum-Guided Reinforcement Learning
Wenjie Li, Yujie Zhang, Haoran Sun +25
Chest X-ray (CXR) imaging is one of the most widely used diagnostic modalities in clinical practice, encompassing a broad spectrum of diagnostic tasks. Recent advancements have see…
Chiron-o1: Igniting Multimodal Large Language Models towards Generalizable Medical Reasoning via Mentor-Intern Collaborative Search
Haoran Sun, Yankai Jiang, Wenjie Lou +6
Multimodal large language models (MLLMs) have begun to demonstrate robust reasoning capabilities on general tasks, yet their application in the medical domain remains in its early…