3 papers
cs.LG2025
LORENZA: Enhancing Generalization in Low-Rank Gradient LLM Training via Efficient Zeroth-Order Adaptive SAM
Yehonathan Refael, Iftach Arbel, Ofir Lindenbaum +1
We study robust parameter-efficient fine-tuning (PEFT) techniques designed to improve accuracy and generalization while operating within strict computational and memory hardware co…
cs.CL2024
TransformLLM: Adapting Large Language Models via LLM-Transformed Reading Comprehension Text
Iftach Arbel, Yehonathan Refael, Ofir Lindenbaum
Large Language Models (LLMs) have shown promise in highly-specialized domains, however challenges are still present in aspects of accuracy and costs. These limitations restrict the…
cs.LG2024
Learning k-Level Structured Sparse Neural Networks Using Group Envelope Regularization
Yehonathan Refael, Iftach Arbel, Wasim Huleihel
The extensive need for computational resources poses a significant obstacle to deploying large-scale Deep Neural Networks (DNN) on devices with constrained resources. At the same t…