4 papers
GRACE:Gradient-guided Coreset Selection for LLM Unlearning
Praveen Bushipaka, Andrea D'Angelo, Lucia Passaro +1
Machine Unlearning methods for Large Language Models typically assume pre-specified forget and retain sets. In realistic settings, however, requests may provide only a few examples…
Standard vs. Modular Sampling: Best Practices for Reliable LLM Unlearning
Praveen Bushipaka, Lucia Passaro, Tommaso Cucinotta
A conventional LLM Unlearning setting consists of two subsets -"forget" and "retain", with the objectives of removing the undesired knowledge from the forget set while preserving t…
Embracing Diversity: A Multi-Perspective Approach with Soft Labels
Benedetta Muscato, Praveen Bushipaka, Gizem Gezici +3
Prior studies show that adopting the annotation diversity shaped by different backgrounds and life experiences and incorporating them into the model learning, i.e. multi-perspectiv…
CloudSim 7G: An Integrated Toolkit for Modeling and Simulation of Future Generation Cloud Computing Environments
Remo Andreoli, Jie Zhao, Tommaso Cucinotta +1
Cloud Computing has established itself as an efficient and cost-effective paradigm for the execution of web-based applications, and scientific workloads, that need elasticity and o…