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20242026
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cs.CV2026

Animation2Code: Evaluating Temporal Visual Reasoning in Video-to-Code Generation

Anya Ji, Abhijith Varma Mudunuri, David M. Chan +1

While recent vision-language models (VLMs) have achieved significant improvements on static visual-to-code tasks such as generating code for webpages, charts, or SVGs, it remains u…

cs.CV2026

ScribbleEdit: Synthetic Data for Image Editing with Scribbles and Text

Anya Ji, George Ma, Téa Wright +4

Recent progress in generative models has significantly advanced image editing capabilities, yet precise and intuitive user control remains difficult. Specifically, users often stru…

cs.CV2026

Attend Before Attention: Efficient and Scalable Video Understanding via Autoregressive Gazing

Baifeng Shi, Stephanie Fu, Long Lian +10

Multi-modal large language models (MLLMs) have advanced general-purpose video understanding but struggle with long, high-resolution videos -- they process every pixel equally in th…

cs.CV2026

VisGym: Diverse, Customizable, Scalable Environments for Multimodal Agents

Zirui Wang, Junyi Zhang, Jiaxin Ge +9

Modern Vision-Language Models (VLMs) remain poorly characterized in multi-step visual interactions, particularly in how they integrate perception, memory, and action over long hori…

cs.CV2025

Constantly Improving Image Models Need Constantly Improving Benchmarks

Jiaxin Ge, Grace Luo, Heekyung Lee +7

Recent advances in image generation, often driven by proprietary systems like GPT-4o Image Gen, regularly introduce new capabilities that reshape how users interact with these mode…

cs.CV2025

TULIP: Towards Unified Language-Image Pretraining

Zineng Tang, Long Lian, Seun Eisape +6

Despite the recent success of image-text contrastive models like CLIP and SigLIP, these models often struggle with vision-centric tasks that demand high-fidelity image understandin…