3 papers
cs.CV2026
RISE: Adaptive Imagination for World Action Models
Hongbo Lu, Liang Yao, Chenghao He +5
World Action Models (WAMs) improve planning by incorporating future world evolution into action generation, yet existing methods allocate a fixed imagination budget to every scene.…
cs.CV2026
The DAWN of World-Action Interactive Models
Hongbo Lu, Liang Yao, Chenghao He +6
A plausible scene evolution depends on the maneuver being considered, while a good maneuver depends on how the scene may evolve. Existing World Action Models (WAMs) largely miss th…
cs.CV2026
Clinical Cognition Alignment for Gastrointestinal Diagnosis with Multimodal LLMs
Huan Zheng, Yucheng Zhou, Tianyi Yan +6
Multimodal Large Language Models (MLLMs) have demonstrated remarkable potential in medical image analysis. However, their application in gastrointestinal endoscopy is currently hin…