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cs.CL2026
Learning an Anchored Prompt Space for Continual Adaptation of Large Language Models
Rongguang Ye, Zhan Zhuang, Yichen Wu +2
Continually adapting large language models requires acquiring new knowledge while preserving previously learned capabilities. Although jointly adapting model parameters and task-sp…
cs.CL2025
One-for-All Pruning: A Universal Model for Customized Compression of Large Language Models
Rongguang Ye, Ming Tang
Existing pruning methods for large language models (LLMs) focus on achieving high compression rates while maintaining model performance. Although these methods have demonstrated sa…