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cs.CV2026

EditStream: A Unified Autoregressive Framework for Interactive Video Generation and Editing

Yuqian Zhou, Zhenghong Zhou, Zongze Wu +5

Interactive video generation and editing are becoming increasingly important for creative design. In this report, we introduce EditStream: a unified framework for interactive video…

cs.CV2026

HiLo-Token: Input-Adaptive High-Low Frequency Token Compression for Efficient Image Editing

Haoran You, Yotam Nitzan, Lingzhi Zhang +8

Creative image editing tools, such as Photoshop's Remove or Generative Fill buttons, are central to everyday customer use and account for a major share of traffic in Photoshop and…

cs.CV2026

Tri-Prompting: Video Diffusion with Unified Control over Scene, Subject, and Motion

Zhenghong Zhou, Xiaohang Zhan, Zhiqin Chen +8

Recent video diffusion models have made remarkable strides in visual quality, yet precise, fine-grained control remains a key bottleneck that limits practical customizability for c…

cs.CV2026

How Long Can Unified Multimodal Models Generate Images Reliably? Taming Long-Horizon Interleaved Image Generation via Context Curation

Haoyu Chen, Qing Liu, Yuqian Zhou +7

Unified multimodal models hold the promise of generating extensive, interleaved narratives, weaving text and imagery into coherent long-form stories. However, current systems suffe…

cs.CV2026

Rethinking Global Text Conditioning in Diffusion Transformers

Nikita Starodubcev, Daniil Pakhomov, Zongze Wu +6

Diffusion transformers typically incorporate textual information via attention layers and a modulation mechanism using a pooled text embedding. Nevertheless, recent approaches disc…

cs.CV2025

Both Semantics and Reconstruction Matter: Making Representation Encoders Ready for Text-to-Image Generation and Editing

Shilong Zhang, He Zhang, Zhifei Zhang +11

Modern Latent Diffusion Models (LDMs) typically operate in low-level Variational Autoencoder (VAE) latent spaces that are primarily optimized for pixel-level reconstruction. To uni…