Sen Cui

From Coefficients to Directions: Rethinking Model Merging with Directional Alignment

Addressing Data Heterogeneity Through a Pre-learned Manifold for Distributed Learning Scenarios

Merging without Forgetting: Continual Fusion of Task-Specific Models via Optimal Transport

Adaptive Localization of Knowledge Negation for Continual LLM Unlearning

Advancing Personalized Learning with Neural Collapse for Long-Tail Challenge

CALM: Consensus-Aware Localized Merging for Multi-Task Learning

Decentralized Dynamic Cooperation of Personalized Models for Federated Continual Learning

Learning without Isolation: Pathway Protection for Continual Learning

Counterfactual Delayed Feedback Learning

Do We Really Need Parameter-Isolation to Protect Task Knowledge?