activity
20242026
collaborators

5 papers

cs.CV2026

Physics-IQ Verified

Tim Rädsch, Yuki M Asano, Hilde Kuehne +4

Video generative models ( VGMs) have become a new frontier that can be used not just for video generation but for a multitude of downstream tasks, including world modeling. To adva…

cs.CV2026

FindIt: A Format-Informed Visual Detection Benchmark for Generalist Multimodal LLMs

Eshika Khandelwal, Jingjing Pan, Mingfang Zhang +3

Multimodal large language models (MLLMs) are predominantly evaluated on free-form vision-language tasks such as visual question answering, captioning, and summarization. However, t…

cs.CV2025

VOLD: Reasoning Transfer from LLMs to Vision-Language Models via On-Policy Distillation

Walid Bousselham, Hilde Kuehne, Cordelia Schmid

Training vision-language models (VLMs) for complex reasoning remains a challenging task, i.a. due to the scarcity of high-quality image-text reasoning data. Conversely, text-based…

cs.CV2025

VisualOverload: Probing Visual Understanding of VLMs in Really Dense Scenes

Paul Gavrikov, Wei Lin, M. Jehanzeb Mirza +6

Is basic visual understanding really solved in state-of-the-art VLMs? We present VisualOverload, a slightly different visual question answering (VQA) benchmark comprising 2,720 que…

cs.CV2024

MaskInversion: Localized Embeddings via Optimization of Explainability Maps

Walid Bousselham, Sofian Chaybouti, Christian Rupprecht +2

Vision-language foundation models such as CLIP have achieved tremendous results in global vision-language alignment, but still show some limitations in creating representations for…