4 papers
Few Channels Draw The Whole Picture: Revealing Massive Activations in Diffusion Transformers
Evelyn Turri, Davide Bucciarelli, Sara Sarto +2
Diffusion Transformers (DiTs) and related flow-based architectures are now among the strongest text-to-image generators, yet the internal mechanisms through which prompts shape ima…
Harnessing Self-Supervised Features for Art Classification
Federico Melis, Davide Bilardello, Emanuele Prato +2
Classifying artworks presents a significant challenge due to the complex interplay of fine-grained details and abstract features that condition the style or genre of an artwork. Th…
RaTA-Tool: Retrieval-based Tool Selection with Multimodal Large Language Models
Gabriele Mattioli, Evelyn Turri, Sara Sarto +3
Tool learning with foundation models aims to endow AI systems with the ability to invoke external resources -- such as APIs, computational utilities, and specialized models -- to s…
Tiny Inference-Time Scaling with Latent Verifiers
Davide Bucciarelli, Evelyn Turri, Lorenzo Baraldi +2
Inference-time scaling has emerged as an effective way to improve generative models at test time by using a verifier to score and select candidate outputs. A common choice is to em…