activity
20232026
most citedImageBind-LLM: Multi-modality Instruction Tuning

25 citations · 25 across the 12 of their papers we have counts for

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Showing cs.CVShow all

8 papers · 1 filter

cs.CV2026

GuideMe: Multi-Domain Task Guidance and Intervention in Streaming Video

Fang Liu, Jinpeng Chen, Ke Xu +7

While multimodal Large Language Models (MLLMs) excel at offline video understanding, an interesting question of how far they are from serving as a real-time procedural coach remain…

cs.CV2026

X-Stream: Exploring MLLMs as Multiplexers for Multi-Stream Understanding

Peiwen Sun, Xudong Lu, Huadai Liu +10

While video streaming understanding has made significant strides, real-world applications, such as live sports broadcasting, autonomous driving, and multi-screen collaboration, inh…

cs.CV2026

AURA: Always-On Understanding and Real-Time Assistance via Video Streams

Xudong Lu, Yang Bo, Jinpeng Chen +9

Video Large Language Models (VideoLLMs) have achieved strong performance on many video understanding tasks, but most existing systems remain offline and are not well-suited for liv…

cs.CV2026

PhoStream: Benchmarking Real-World Streaming for Omnimodal Assistants in Mobile Scenarios

Xudong Lu, Huankang Guan, Yang Bo +10

Multimodal Large Language Models excel at offline audio-visual understanding, but their ability to serve as mobile assistants in continuous real-world streams remains underexplored…

cs.CV2025

GLEAM: Learning to Match and Explain in Cross-View Geo-Localization

Xudong Lu, Zhi Zheng, Yi Wan +11

Cross-View Geo-Localization (CVGL) focuses on identifying correspondences between images captured from distinct perspectives of the same geographical location. However, existing CV…

cs.CV2025

Adaptive Markup Language Generation for Contextually-Grounded Visual Document Understanding

Han Xiao, Yina Xie, Guanxin Tan +12

Visual Document Understanding has become essential with the increase of text-rich visual content. This field poses significant challenges due to the need for effective integration…