6 papers · 1 filter
Knowledge Distillation for Visual Autoregressive Models
Elia Peruzzo, Aritra Bhowmik, Guillaume Sautiere +2
Autoregressive (AR) image generation models are highly expressive but computationally intensive, motivating effective model compression. Knowledge distillation (KD) is a natural ap…
Multi-Scale Local Speculative Decoding for Image Generation
Elia Peruzzo, Guillaume Sautière, Amirhossein Habibian
Autoregressive (AR) models have achieved remarkable success in image synthesis, yet their sequential nature imposes significant latency constraints. Speculative Decoding offers a p…
Safe Vision-Language Models via Unsafe Weights Manipulation
Moreno D'IncÃ, Elia Peruzzo, Xingqian Xu +3
Vision-language models (VLMs) often inherit the biases and unsafe associations present within their large-scale training dataset. While recent approaches mitigate unsafe behaviors,…
RAGME: Retrieval Augmented Video Generation for Enhanced Motion Realism
Elia Peruzzo, Dejia Xu, Xingqian Xu +2
Video generation is experiencing rapid growth, driven by advances in diffusion models and the development of better and larger datasets. However, producing high-quality videos rema…
GradBias: Unveiling Word Influence on Bias in Text-to-Image Generative Models
Moreno D'IncÃ, Elia Peruzzo, Massimiliano Mancini +3
Recent progress in Text-to-Image (T2I) generative models has enabled high-quality image generation. As performance and accessibility increase, these models are gaining significant…
OpenBias: Open-set Bias Detection in Text-to-Image Generative Models
Moreno D'IncÃ, Elia Peruzzo, Massimiliano Mancini +6
Text-to-image generative models are becoming increasingly popular and accessible to the general public. As these models see large-scale deployments, it is necessary to deeply inves…