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cs.LG2026
Self-Boosting Vision-Language Models with Noisy Student On-Policy Self-Distillation
Shuai Wang, Daoan Zhang, Zhe Tang +2
Post-training enables vision-language models (VLMs) to understand human instructions and perform various downstream tasks. Current post-training methods usually rely on human-annot…
cs.LG2024
Reassessing Layer Pruning in LLMs: New Insights and Methods
Yao Lu, Hao Cheng, Yujie Fang +6
Although large language models (LLMs) have achieved remarkable success across various domains, their considerable scale necessitates substantial computational resources, posing sig…