3 papers
cs.LG2026
Low-Rank Adapters Initialization via Gradient Surgery for Continual Learning
Joana Pasquali, Ramiro N. Barros, Arthur S. Bianchessi +7
LoRA is widely adopted for continual fine-tuning of Large Language Models due to its parameter efficiency, modularity across tasks, and compatibility with replay strategies. Howeve…
cs.LG2026
Inference-Time Machine Unlearning via Gated Activation Redirection
Vinícius Conte Turani, Otávio Parraga, João Vitor Boer Abitante +7
Large Language Models memorize vast amounts of training data, raising concerns regarding privacy, copyright infringement, and safety. Machine unlearning seeks to remove the influen…
cs.LG2026
Quantization-Robust LLM Unlearning via Low-Rank Adaptation
João Vitor Boer Abitante, Joana Meneguzzo Pasquali, Luan Fonseca Garcia +4
Large Language Model (LLM) unlearning aims to remove targeted knowledge from a trained model, but practical deployments often require post-training quantization (PTQ) for efficient…