3 papers
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…
cs.CV2025
A Framework for Benchmarking Fairness-Utility Trade-offs in Text-to-Image Models via Pareto Frontiers
Marco N. Bochernitsan, Rodrigo C. Barros, Lucas S. Kupssinskü
Achieving fairness in text-to-image generation demands mitigating social biases without compromising visual fidelity, a challenge critical to responsible AI. Current fairness evalu…
cs.GR2025
Inference Time Debiasing Concepts in Diffusion Models
Lucas S. Kupssinskü, Marco N. Bochernitsan, Jordan Kopper +2
We propose DeCoDi, a debiasing procedure for text-to-image diffusion-based models that changes the inference procedure, does not significantly change image quality, has negligible…