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cs.LG2025
Achieving binary weight and activation for LLMs using Post-Training Quantization
Siqing Song, Chuang Wang, Ruiqi Wang +2
Quantizing large language models (LLMs) to 1-bit precision significantly reduces computational costs, but existing quantization techniques suffer from noticeable performance degrad…
cs.LG2025
Adversarial Mixup Unlearning
Zhuoyi Peng, Yixuan Tang, Yi Yang
Machine unlearning is a critical area of research aimed at safeguarding data privacy by enabling the removal of sensitive information from machine learning models. One unique chall…