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cs.CV2026

REZE: Recognition-Based Zero-Shot Extraction for Video Temporal Grounding

Boyang Li, Chenhui Gou, Jianfei Cai

Video temporal grounding (VTG) refers to the task of identifying the time interval in a video that corresponds to a given natural-language query. A common zero-shot strategy asks a…

cs.CV2026

UniMedVL: Unifying Medical Multimodal Understanding and Generation through Observation-Knowledge-Analysis

Junzhi Ning, Wei Li, Cheng Tang +24

Medical workflows routinely combine reading images with producing visual and textual outputs, making both image understanding and generation central to medical AI. Most existing sy…

cs.CV2026

LiveWorld: Simulating Out-of-Sight Dynamics in Generative Video World Models

Zicheng Duan, Jiatong Xia, Zeyu Zhang +7

Recent generative video world models aim to simulate visual environment evolution, allowing an observer to interactively explore the scene via camera control. However, they implici…

cs.CV2026

Mobile-VideoGPT: Fast and Accurate Model for Mobile Video Understanding

Abdelrahman Shaker, Muhammad Maaz, Chenhui Gou +3

Video understanding models often struggle with high computational requirements, extensive parameter counts, and slow inference speed, making them inefficient for practical use. To…

cs.CV2025

VQ-VA World: Towards High-Quality Visual Question-Visual Answering

Chenhui Gou, Zilong Chen, Zeyu Wang +10

This paper studies Visual Question-Visual Answering (VQ-VA): generating an image, rather than text, in response to a visual question -- an ability that has recently emerged in prop…

cs.CV2025

LightFusion: A Light-weighted, Double Fusion Framework for Unified Multimodal Understanding and Generation

Zeyu Wang, Zilong Chen, Chenhui Gou +8

Unified multimodal models have recently shown remarkable gains in both capability and versatility, yet most leading systems are still trained from scratch and require substantial c…