collaborators

5 papers

cs.CV2026

WaiT for the Signal: Simple Frequency-Aware Flow-Matching

Krunoslav Lehman Pavasovic, Théophane Vallaeys, Stéphane Mallat +4

As image generation models scale to ever higher resolutions, global coherence, local detail, and texture fidelity become critical axes for generation quality. However, standard flo…

cs.CV2026

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization

Théophane Vallaeys, Jakob Verbeek, Matthieu Cord

Tokenizers are a key component of state-of-the-art generative image models, extracting the most important features from the signal while reducing data dimension and redundancy. Mos…

cs.CV2026

Beyond Language Modeling: An Exploration of Multimodal Pretraining

Shengbang Tong, David Fan, John Nguyen +18

The visual world offers a critical axis for advancing foundation models beyond language. Despite growing interest in this direction, the design space for native multimodal models r…

cs.CV2025

VUGEN: Visual Understanding priors for GENeration

Xiangyi Chen, Théophane Vallaeys, Maha Elbayad +2

Recent advances in Vision-Language Models (VLMs) have enabled unified understanding across text and images, yet equipping these models with robust image generation capabilities rem…

cs.LG2025

Qinco2: Vector Compression and Search with Improved Implicit Neural Codebooks

Théophane Vallaeys, Matthew Muckley, Jakob Verbeek +1

Vector quantization is a fundamental technique for compression and large-scale nearest neighbor search. For high-accuracy operating points, multi-codebook quantization associates d…