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cs.CV2024
Contextuality Helps Representation Learning for Generalized Category Discovery
Tingzhang Luo, Mingxuan Du, Jiatao Shi +3
This paper introduces a novel approach to Generalized Category Discovery (GCD) by leveraging the concept of contextuality to enhance the identification and classification of catego…
cs.CV2024
Effective Prompt Pool Learning for Continual Category Discovery
Fernando Julio Cendra, Xinghui Li, Kai Han
This paper studies effective prompt pool learning for Continual Category Discovery (CCD), a challenging open-world setting where a model must discover novel categories from a conti…
cs.LG2024
Beyond the Known: Novel Class Discovery for Open-world Graph Learning
Yucheng Jin, Yun Xiong, Juncheng Fang +5
Node classification on graphs is of great importance in many applications. Due to the limited labeling capability and evolution in real-world open scenarios, novel classes can emer…