Théophane Vallaeys — accepted AI-conference papers

2026

Towards Unified Multimodal Pretraining

Shengbang Tong, David Fan, John Nguyen, Ellis Brown, Gaoyue Zhou, Shengyi Qian +14

ICML 2026spotlight

Unified multimodal models aim to input and output both vision and language data within a single system. In this work, we explore the design space of Unified Multimodal Pretraining through a controlled, from-scratch study. We find that leveraging a single high-dimensional semantic encoder (e.g. SigLI…

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2025

Qinco2: Vector Compression and Search with Improved Implicit Neural Codebooks

Théophane Vallaeys, Matthew J. Muckley, Jakob Verbeek, Matthijs Douze

ICLR 2025poster

Vector quantization is a fundamental technique for compression and large-scale nearest neighbor search. For high-accuracy operating points, multi-codebook quantization associates data vectors with one element from each of multiple codebooks. An example is residual quantization (RQ), which iterative…

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