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20242026
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23 citations · 26 across the 23 of their papers we have counts for

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cs.CV2026

DataComp-VLM: Improved Open Datasets for Vision-Language Models

Matteo Farina, Vishaal Udandarao, Thao Nguyen +33

Building performant Vision-Language Models (VLMs) requires carefully curating large-scale training datasets, yet the community lacks systematic benchmarks for evaluating such curat…

cs.CV2026

Personalizing Text-to-Image Generation to Individual Taste

Anne-Sofie Maerten, Juliane Verwiebe, Shyamgopal Karthik +3

Modern text-to-image (T2I) models generate high-fidelity visuals but remain indifferent to individual user preferences. While existing reward models optimize for "average" human ap…

cs.CV20251 cited

Solving Spatial Supersensing Without Spatial Supersensing

Vishaal Udandarao, Shyamgopal Karthik, Surabhi S. Nath +3

Cambrian-S aims to take the first steps towards improving video world models with spatial supersensing by introducing (i) two benchmarks, VSI-Super-Recall (VSR) and VSI-Super-Count…

cs.CV2025

Are We Done with Object-Centric Learning?

Alexander Rubinstein, Ameya Prabhu, Matthias Bethge +1

Object-centric learning (OCL) seeks to learn representations that only encode an object, isolated from other objects or background cues in a scene. This approach underpins various…

cs.CV2024

A Practitioner's Guide to Continual Multimodal Pretraining

Karsten Roth, Vishaal Udandarao, Sebastian Dziadzio +7

Multimodal foundation models serve numerous applications at the intersection of vision and language. Still, despite being pretrained on extensive data, they become outdated over ti…