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Yu-Cheng Shi

2 accepted papers

2026

AREA: Attribute Extraction and Aggregation for CLIP-Based Class-Incremental Learning

ICML 2026poster

Class-Incremental Learning (CIL) is important in building real-world learning systems. In CLIP-based CIL, the model performs classification by comparing similarity between visual and textual embeddings obtained from template prompts, e.g., ``a photo of a [CLASS]''. This seemingly monolithic matching…

Cited by 0SourceScholar
2026

SAME: Stabilized Mixture-of-Experts for Multimodal Continual Instruction Tuning

ICML 2026poster

Multimodal Large Language Models (MLLMs) achieve strong performance through instruction tuning, but real-world deployment requires them to continually expand their capabilities, making Multimodal Continual Instruction Tuning (MCIT) essential. Recent methods leverage sparse expert routing to promote …

Cited by 0SourceScholar