2 papers
cs.CL2026
Learning New Facts with QLoRA: An Acquisition-Retention Frontier
Estelle Zheng, Sébastien Warichet, Emmanuel Helbert +1
Parameter-efficient fine-tuning is often assumed to preserve pretrained capabilities because it updates only a small number of parameters. We show that this assumption depends stro…
cs.CL2025
Ladder Up, Memory Down: Low-Cost Fine-Tuning With Side Nets
Estelle Zheng, Nathan Cerisara, Sébastien Warichet +3
Fine-tuning large language models (LLMs) is often limited by the memory available on commodity GPUs. Parameter-efficient fine-tuning (PEFT) methods such as QLoRA reduce the number…