Tianyu Liu

State-of-the-art VLMs struggle to execute scientific research workflows, revealing a critical gap in their ability to interact with specialized software and produce verifiable results.

Conditioning video world models on continuous tactile dynamics cuts hand-motion underestimation from 23% to 9%—and surprisingly boosts visual prediction accuracy even when touch sensors are removed at inference.

Grounding policy optimization in canonical disease graphs allows a compact 9B model to outperform GPT-5.5 on long-tail clinical diagnosis, revealing that controlled evidence routing matters far more than raw retrieval volume.