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cs.LG2024
SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning
Jinghan Jia, Yihua Zhang, Yimeng Zhang +5
Large Language Models (LLMs) have highlighted the necessity of effective unlearning mechanisms to comply with data regulations and ethical AI practices. LLM unlearning aims at remo…
cs.LG2024★ 1 cited
From PEFT to DEFT: Parameter Efficient Finetuning for Reducing Activation Density in Transformers
Bharat Runwal, Tejaswini Pedapati, Pin-Yu Chen
Pretrained Language Models (PLMs) have become the de facto starting point for fine-tuning on downstream tasks. However, as model sizes continue to increase, traditional fine-tuning…