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cs.LG2025
Breaking the Compression Ceiling: Data-Free Pipeline for Ultra-Efficient Delta Compression
Xiaohui Wang, Peng Ye, Chenyu Huang +5
With the rise of the fine-tuned-pretrained paradigm, storing numerous fine-tuned models for multi-tasking creates significant storage overhead. Delta compression alleviates this by…
cs.LG2024
On the Emergence of Cross-Task Linearity in the Pretraining-Finetuning Paradigm
Zhanpeng Zhou, Zijun Chen, Yilan Chen +2
The pretraining-finetuning paradigm has become the prevailing trend in modern deep learning. In this work, we discover an intriguing linear phenomenon in models that are initialize…