Datasets:
Tasks:
Video Classification
Modalities:
Video
Languages:
English
Size:
< 1K
Tags:
temporal-localization
video-understanding
multimodal
multimodal-safety
content-moderation
long-video
License:
Commit History
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Verified signatureTHVL-Bench: A Multimodal Benchmark for Temporal Localization of Harmful Content in Long Videos ## Introduction Video-level safety assessment is often insufficient for real-world moderation because harmful content is typically sparse and temporally localized. We introduce **Temporal Harmful Video Localization (THVL)**, a task requiring models to identify harmful segments with precise temporal boundaries and multimodal rationales. ## Dataset Summary **THVL-Bench** is a comprehensive benchmark designed to evaluate the capability of Multimodal Large Language Models (MLLMs) in detecting and localizing harmful content within long-form videos. - **Total Videos**: 450 real-world long videos sourced from YouTube and Bilibili. - **Annotations**: 1,099 manually annotated segments with precise start/end timestamps. - **Categories**: 11 distinct harm categories reflecting diverse online safety challenges. - **Key Feature**: Each segment includes multimodal rationales (visual/audio) explaining the…1feee27
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