Papers by James Jianqiao Yu

1 papers
ImPart: Importance-Aware Delta-Sparsification for Improved Model Compression and Merging in LLMs (2025.acl-long)

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Challenge: Recent approaches to reduce resource requirements for task-specific large language models have been developed.
Approach: They propose a delta compression approach that optimizes for importance of a model . they use SVD to dynamically adjust the sparsity ratios of different vectors based on their importance .
Outcome: The proposed approach achieves state-of-the-art in retaining task-specific knowledge even at high sparsity ratios.

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