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cs.CV2025
MedFact-R1: Towards Factual Medical Reasoning via Pseudo-Label Augmentation
Gengliang Li, Rongyu Chen, Bin Li +2
Ensuring factual consistency and reliable reasoning remains a critical challenge for medical vision-language models. We introduce MEDFACT-R1, a two-stage framework that integrates…
cs.CV2025★ 1 cited
A Temporal Modeling Framework for Video Pre-Training on Video Instance Segmentation
Qing Zhong, Peng-Tao Jiang, Wen Wang +3
Contemporary Video Instance Segmentation (VIS) methods typically adhere to a pre-train then fine-tune regime, where a segmentation model trained on images is fine-tuned on videos.…
cs.CV2025
Condensing Action Segmentation Datasets via Generative Network Inversion
Guodong Ding, Rongyu Chen, Angela Yao
This work presents the first condensation approach for procedural video datasets used in temporal action segmentation. We propose a condensation framework that leverages generative…