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cs.CV2026

OpenWorldLib: A Unified Codebase and Definition of Advanced World Models

DataFlow Team, Bohan Zeng, Daili Hua +39

World models have garnered significant attention as a promising research direction in artificial intelligence, yet a clear and unified definition remains lacking. In this paper, we…

cs.CV2026

TraceAV-Bench: Benchmarking Multi-Hop Trajectory Reasoning over Long Audio-Visual Videos

Hengyi Feng, Hao Liang, Mingrui Chen +6

Real-world audio-visual understanding requires chaining evidence that is sparse, temporally dispersed, and split across the visual and auditory streams, whereas existing benchmarks…

cs.CV2025

Generative Giants, Retrieval Weaklings: Why do Multimodal Large Language Models Fail at Multimodal Retrieval?

Hengyi Feng, Zeang Sheng, Meiyi Qiang +2

Despite the remarkable success of multimodal large language models (MLLMs) in generative tasks, we observe that they exhibit a counterintuitive deficiency in the zero-shot multimod…

cs.CV2025

LoVR: A Benchmark for Long Video Retrieval in Multimodal Contexts

Qifeng Cai, Hao Liang, Zhaoyang Han +6

Long videos contain a vast amount of information, making video-text retrieval an essential and challenging task in multimodal learning. However, existing benchmarks suffer from lim…

cs.CV2024

MathScape: Benchmarking Multimodal Large Language Models in Real-World Mathematical Contexts

Hao Liang, Linzhuang Sun, Minxuan Zhou +7

With the rapid progress of Multimodal LLMs, evaluating their mathematical reasoning capabilities has become an increasingly important research direction. In particular, visual-text…