Fei Teng

The paper demonstrates that while distilling large language models for medical QA can significantly improve final answer accuracy, this gain often comes at the cost of factual accuracy and detailed reasoning within the generated thought trace.

This paper introduces PS-Track, a hierarchical pipeline for point-supervised Multi-Object Tracking (PS-MOT), which addresses spatial ambiguity and identity drift through Temporal-Feedback Prompting (TFP), Point-Excited Wavelet Attention (PEWA), and Uncertainty-Guided Gaussian Learning (UGL).