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cs.CV2026

ShotFinder: Imagination-Driven Open-Domain Video Shot Retrieval via Web Search

Tao Yu, Haopeng Jin, Hao Wang +18

In recent years, large language models (LLMs) have made rapid progress in information retrieval, yet existing research has mainly focused on text or static multimodal settings. Ope…

cs.CV2026

Beyond Closed-Pool Video Retrieval: A Benchmark and Agent Framework for Real-World Video Search and Moment Localization

Tao Yu, Yujia Yang, Haopeng Jin +17

Traditional video retrieval benchmarks focus on matching precise descriptions to closed video pools, failing to reflect real-world searches characterized by fuzzy, multi-dimensiona…

cs.CV2026

Research on World Models Is Not Merely Injecting World Knowledge into Specific Tasks

Bohan Zeng, Kaixin Zhu, Daili Hua +24

World models have emerged as a critical frontier in AI research, aiming to enhance large models by infusing them with physical dynamics and world knowledge. The core objective is t…

cs.CV2025

The Unseen Bias: How Norm Discrepancy in Pre-Norm MLLMs Leads to Visual Information Loss

Bozhou Li, Xinda Xue, Sihan Yang +5

Multimodal Large Language Models (MLLMs), which couple pre-trained vision encoders and language models, have shown remarkable capabilities. However, their reliance on the ubiquitou…

cs.CV2025

VABench: A Comprehensive Benchmark for Audio-Video Generation

Daili Hua, Xizhi Wang, Bohan Zeng +6

Recent advances in video generation have been remarkable, enabling models to produce visually compelling videos with synchronized audio. While existing video generation benchmarks…

cs.CV2025

AVoCaDO: An Audiovisual Video Captioner Driven by Temporal Orchestration

Xinlong Chen, Yue Ding, Weihong Lin +9

Audiovisual video captioning aims to generate semantically rich descriptions with temporal alignment between visual and auditory events, thereby benefiting both video understanding…