activity
20242026
collaborators

21 papers

cs.CV2026

LoomVideo: Unifying Multimodal Inputs into Video Generation and Editing

Jianzong Wu, Hao Lian, Jiongfan Yang +12

Developing unified video generation and editing models capable of interpreting interleaved multimodal inputs is a promising yet challenging frontier field. Existing unified framewo…

cs.LG2026

Muddit: Liberating Generation Beyond Text-to-Image with a Unified Discrete Diffusion Model

Qingyu Shi, Jinbin Bai, Zhuoran Zhao +7

Unified generation models aim to handle diverse tasks across modalities -- such as text generation, image generation, and vision-language reasoning -- within a single architecture…

cs.LG2026

Towards Customized Multimodal Role-Play

Chao Tang, Jianzong Wu, Qingyu Shi +5

Unified multimodal understanding and generation models enable richer human-AI interaction. Yet jointly customizing a character's persona, dialogue style, and visual identity while…

cs.CV2026

VideoZeroBench: Probing the Limits of Video MLLMs with Spatio-Temporal Evidence Verification

Jiahao Meng, Tan Yue, Qi Xu +7

Recent video multimodal large language models achieve impressive results across various benchmarks. However, current evaluations suffer from two critical limitations: (1) inflated…

cs.CV2026

Rethinking Vector Field Learning for Generative Segmentation

Chaoyang Wang, Yaobo Liang, Boci Peng +3

Taming diffusion models for generative segmentation has attracted increasing attention. While existing approaches primarily focus on architectural tweaks or training heuristics, th…

cs.CV2026

Open-o3-Video: Grounded Video Reasoning with Explicit Spatio-Temporal Evidence

Jiahao Meng, Xiangtai Li, Haochen Wang +8

Most video reasoning models only generate textual reasoning traces without indicating when and where key evidence appears. Recent models such as OpenAI-o3 have sparked wide interes…