Yunzhi Zhuge

A training-free framework that combines a query-independent layout-derived interaction prior with instruction relevance and feature novelty to rank visual evidence according to both potential future utility and diversity, allowing retained visual evidence to shrink monotonically across budgets while remaining reusable throughout the trajectory.

A unified framework that effectively fuses RGB and event data can drastically improve person re-identification accuracy across different camera views.

GROVE achieves state-of-the-art performance in memory retrieval for wearable assistants by seamlessly integrating reactive and proactive memory access from continuous video streams.