activity
20242026
collaborators

21 papers

cs.CV2026

Instruction-Based Video Editing by Repurposing an Image Editing Model

Yunpeng Bai, Yossi Gandelsman, Michaël Gharbi +1

Instruction-based video editing is commonly built on video-pretrained generative backbones: a video diffusion transformer is adapted, at considerable cost, to condition on a source…

cs.LG2026

Learning Sampling Parameters for Diffusion Models

Arisrei Lim, Yossi Gandelsman

Text-to-image diffusion models expose many inference-time sampling parameters, including prompts, negative prompts, classifier-free guidance scales, and noise schedules. These para…

cs.CV2026

Test-Time Training for Modality Order Consistency in Vision-Language Models

Aditi Gupta, Yossi Gandelsman

We find that vision-language models are sensitive to a specific semantically irrelevant change: the order in which the image and question are presented. Across three models and thr…

cs.CV2026

DuSPiT: Dual-Branch Sub-Patch Pixel Diffusion Transformer

Yunpeng Bai, Yossi Gandelsman, Michaël Gharbi

Diffusion Transformers achieve strong image generation performance, but most operate in compressed latent spaces. Pixel-space diffusion avoids this information loss, yet existing a…

cs.LG2026

Neuron Populations Exhibit Divergent Selectivity with Scale

Amil Dravid, Yasaman Bahri, Alexei A. Efros +1

We investigate whether neuron populations within neural networks evolve predictably with scale, extending scaling laws beyond macroscopic observables such as loss. To probe this qu…

cs.CV2026

Jailbreaking Vision-Language Models Through the Visual Modality

Aharon Azulay, Jan Dubiński, Zhuoyun Li +2

The visual modality of vision-language models (VLMs) is an underexplored attack surface for bypassing safety alignment. We introduce four jailbreak attacks exploiting the vision co…