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7 papers · 1 filter

cs.CV2026

Segment Where You Look: Attention as the Interface Between Language Models and Segmenters

Eslam Abdelrahman, Hamza Omar Alkaf, Yuheng Li +5

Vision-language models (VLMs) that segment from language must pass the location of the referent to a pixel decoder. The dominant interface compresses it into the hidden state of a…

cs.CV2026

Pristine Models

Anirudh Sundara Rajan, Krishna Kumar Singh, Richard Zhang +1

Training on broad, unfiltered data enables high-quality image generation, but can also teach models concepts that should not be generated; restricting the training data ensures saf…

cs.CV2026

Streaming Multi-Agent Autoregressive Diffusion Model with World State Registers

Sicheng Mo, Yuheng Li, Ziyang Leng +2

Multi-agent interactive world models should not only generate consistent observations, but also maintain world states that persist across agents and evolve across views. Existing a…

cs.CV2026

UniTemp: Unlocking Video Generation in Any Temporal Order via Bidirectional Distillation

Lin Zhang, Sicheng Mo, Zefan Cai +6

Autoregressive video diffusion models have emerged as a promising approach for long video generation, achieving strong performance in streaming settings. However, existing methods…

cs.CV2026

Personal AI Agent for Camera Roll VQA

Thao Nguyen, Krishna Kumar Singh, Donghyun Kim +2

We study the personal camera roll visual question answering setting. In this setting, a conversational AI assistant can access a user's personal camera roll and retrieve relevant p…

cs.CV2026

MAOAM: Unified Object and Material Selection with Vision-Language Models

Jaden Park, Valentin Deschaintre, Jason Kuen +5

Selection is a core operation in interactive image editing. To be practical, a user should be able to specify and disambiguate the desired selection region through either text or c…

cs.CV2026

From Plans to Pixels: Learning to Plan and Orchestrate for Open-Ended Image Editing

Anirudh Sundara Rajan, Krishna Kumar Singh, Yong Jae Lee

Modern image editing models produce realistic results but struggle with abstract, multi step instructions (e.g., ``make this advertisement more vegetarian-friendly''). Prior agent…