collaborators

12 papers

cs.CV2026

SpatialThinker: Reinforcing Scene Graph-Grounded Spatial Reasoning via Dense Rewards

Hunar Batra, Haoqin Tu, Hardy Chen +3

Multimodal large language models (MLLMs) have achieved remarkable progress in vision-language tasks, but continue to struggle with spatial reasoning. Existing spatial MLLMs rely on…

cs.CV2026

VisualClaw: A Real-Time, Personalized Agent for the Physical World

Haoqin Tu, Jianwen Chen, Zijun Wang +14

Vision language models are serving as general-purpose interfaces for complex multimodal tasks. However, deployment still faces three gaps: VLMs typically incur high latency and cos…

cs.AI2026

AutoMedBench: Towards Medical AutoResearch with Agentic AI Models

Junqi Liu, Selena Song, Yuhan Wang +12

Autonomous agents are increasingly expected to support end-to-end medical-AI research workflows, moving beyond isolated prediction tasks or short-form clinical question answering.…

cs.CL2026

Reasoning While Asking: Transforming Reasoning Large Language Models from Passive Solvers to Proactive Inquirers

Xin Chen, Feng Jiang, Yiqian Zhang +5

Reasoning-oriented Large Language Models (LLMs) have achieved remarkable progress with Chain-of-Thought (CoT) prompting, yet they remain fundamentally limited by a \emph{blind self…

cs.CL2026

From Seeing to Thinking: Decoupling Perception and Reasoning Improves Post-Training of Vision-Language Models

Juncheng Wu, Hardy Chen, Haoqin Tu +6

Recent advances in vision-language models (VLMs) emphasize long chain-of-thought reasoning; yet, we find that their performance on visual tasks is primarily limited by a lack of vi…

cs.CL2026

ClinSeekAgent: Automating Multimodal Evidence Seeking for Agentic Clinical Reasoning

Juncheng Wu, Letian Zhang, Yuhan Wang +5

Large language models (LLMs) and agentic systems have shown promise for clinical decision support, but existing works largely assume that evidence has already been curated and hand…