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cs.LG2024
Fast Forwarding Low-Rank Training
Adir Rahamim, Naomi Saphra, Sara Kangaslahti +1
Parameter efficient finetuning methods like low-rank adaptation (LoRA) aim to reduce the computational costs of finetuning pretrained Language Models (LMs). Enabled by these low-ra…
cs.LG2022
Robustness through Cognitive Dissociation Mitigation in Contrastive Adversarial Training
Adir Rahamim, Itay Naeh
In this paper, we introduce a novel neural network training framework that increases model's adversarial robustness to adversarial attacks while maintaining high clean accuracy by…