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cs.CV2026

Frames2LoRA: Parametric Video Internalization for Vision-Language Models

Manan Suri, Sarvesh Baskar, Dinesh Manocha

Processing video in vision-language models is expensive: each frame occupies hundreds of tokens, and inference cost scales with every frame and every repeated query. We introduce F…

cs.CV2026

DRAGON: A Benchmark for Evidence-Grounded Visual Reasoning over Diagrams

Anirudh Iyengar Kaniyar Narayana Iyengar, Tampu Ravi Kumar, Gaurav Najpande +4

Diagram question answering (DQA) requires models to interpret structured visual representations such as charts, maps, infographics, circuit schematics, and scientific diagrams. Rec…

cs.CV2026

Learning Illumination Control in Diffusion Models

Nishit Anand, Manan Suri, Christopher Metzler +2

Controlling illumination in images is essential for photography and visual content creation. While closed-source models have demonstrated impressive illumination control, open-sour…

cs.CV2026

InfinityStory: Unlimited Video Generation with World Consistency and Character-Aware Shot Transitions

Mohamed Elmoghany, Liangbing Zhao, Xiaoqian Shen +27

Generating long-form storytelling videos with consistent visual narratives remains a significant challenge in video synthesis. We present a novel framework, dataset, and a model th…

cs.CV2025

A Survey on Long-Video Storytelling Generation: Architectures, Consistency, and Cinematic Quality

Mohamed Elmoghany, Ryan Rossi, Seunghyun Yoon +26

Despite the significant progress that has been made in video generative models, existing state-of-the-art methods can only produce videos lasting 5-16 seconds, often labeled "long-…