2 citations · 2 across the 7 of their papers we have counts for
3 papers · 1 filter
Synesthesia via Direct Latent Augmentation:Bypassing the Decode-Encode Loop for Cross-Modal Distillation
Cristian Sbrolli, Nicolas Michel, Matteo Matteucci +1
While multimodal integration significantly improves computer vision models, deploying them incurs prohibitive inference costs and requires scarce, perfectly paired datasets. Recent…
Beyond Bag-of-Words: Diagnosing Compositional Binding Failures in Vision-Language Models
Cristian Sbrolli, Matteo Matteucci, Toshihiko Yamasaki
Modern vision-language models struggle with basic compositional reasoning, failing to bind attributes to objects or relations to their referents. Existing benchmarks either rely on…
PolyGen: Fully Synthetic Vision-Language Training via Multi-Generator Ensembles
Leonardo Brusini, Cristian Sbrolli, Eugenio Lomurno +2
Synthetic data offers a scalable solution for vision-language pre-training, yet current state-of-the-art methods typically rely on scaling up a single generative backbone, which in…