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20232026
most citedVideo Understanding with Large Language Models: A Survey

8 citations · 19 across the 22 of their papers we have counts for

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19 papers · 1 filter

cs.CV2026

AdaTurn: Budget-Aware Test-Time Scaling for Active Visual Perception Agents

Susan Liang, Chao Huang, Filippos Bellos +3

Active visual agents solve fine-grained image tasks by interleaving reasoning with image-grounding actions across multiple turns. However, deployment-time rollout budgets are rarel…

cs.CV2026

Omni-Judge: Can Omni-LLMs Serve as Human-Aligned Judges for Text-Conditioned Audio-Video Generation?

Susan Liang, Chao Huang, Filippos Bellos +7

State-of-the-art text-to-video generation models such as Sora 2 and Veo 3 can now produce high-fidelity videos with synchronized audio directly from a textual prompt, marking a new…

cs.CV2025

Video-R4: Reinforcing Text-Rich Video Reasoning with Visual Rumination

Yolo Y. Tang, Daiki Shimada, Hang Hua +4

Understanding text-rich videos requires reading small, transient textual cues that often demand repeated inspection. Yet most video QA models rely on single-pass perception over fi…

cs.CV2025

Video-LMM Post-Training: A Deep Dive into Video Reasoning with Large Multimodal Models

Yolo Y. Tang, Jing Bi, Pinxin Liu +24

Video understanding represents the most challenging frontier in computer vision, requiring models to reason about complex spatiotemporal relationships, long-term dependencies, and…

cs.CV2025

When to Think and When to Look: Uncertainty-Guided Lookback

Jing Bi, Filippos Bellos, Junjia Guo +8

Test-time thinking (that is, generating explicit intermediate reasoning chains) is known to boost performance in large language models and has recently shown strong gains for large…

cs.CV2025

High-Quality Sound Separation Across Diverse Categories via Visually-Guided Generative Modeling

Chao Huang, Susan Liang, Yapeng Tian +2

We propose DAVIS, a Diffusion-based Audio-VIsual Separation framework that solves the audio-visual sound source separation task through generative learning. Existing methods typica…