3 papers
cs.CV2025
Knowledge Swapping via Learning and Unlearning
Mingyu Xing, Lechao Cheng, Shengeng Tang +3
We introduce \textbf{Knowledge Swapping}, a novel task designed to selectively regulate knowledge of a pretrained model by enabling the forgetting of user\-specified information, r…
cs.CV2025
Navigating Semantic Drift in Task-Agnostic Class-Incremental Learning
Fangwen Wu, Lechao Cheng, Shengeng Tang +4
Class-incremental learning (CIL) seeks to enable a model to sequentially learn new classes while retaining knowledge of previously learned ones. Balancing flexibility and stability…
cs.CV2025
Efficient Vision Language Model Fine-tuning for Text-based Person Anomaly Search
Jiayi He, Shengeng Tang, Ao Liu +3
This paper presents the HFUT-LMC team's solution to the WWW 2025 challenge on Text-based Person Anomaly Search (TPAS). The primary objective of this challenge is to accurately iden…