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YongCheng Zhong

2 accepted papers

2026

Learning Adaptive and Expandable Mixture Model for Continual Learning

AAAI 2026technical

Continuous learning constitutes a fundamental capability of artificial intelligence systems, enabling them to incrementally assimilate novel information without succumbing to catastrophic forgetting. Recent research has leveraged Pre-Trained Models (PTMs) to enhance continual learning efficacy. Neve

Cited by 0SourcePDFScholar
2025

Learning Multi-Source and Robust Representations for Continual Learning

NeurIPS 2025poster

Plasticity and stability denote the ability to assimilate new tasks while preserving previously acquired knowledge, representing two important concepts in continual learning. Recent research addresses stability by leveraging pre-trained models to provide informative representations, yet the efficacy…

Cited by 0SourcecodeScholar