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Multimodal Intelligence Lab
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- United States of America
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- Video-Comprehension-Score
Video-Comprehension-Score PublicVCS is a Python library specifically designed to overcome these challenges by evaluating narrative comprehension through direct comparison of extensive, detailed video descriptions generated by LVL…
- CLIP-CC-Bench
CLIP-CC-Bench PublicEvaluation framework and leaderboard for paragraph-level, minute-scale video description: 200 movie clips, 17 video-language models, 5 embedding judges (EvalMG @ SIGIR 2026).
Python 1
- mint-brand
mint-brand PublicJavaScript
Repositories
- CLIP-CC-Bench Public
Evaluation framework and leaderboard for paragraph-level, minute-scale video description: 200 movie clips, 17 video-language models, 5 embedding judges (EvalMG @ SIGIR 2026).
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Multimodal-Intelligence-Lab/CLIP-CC-Bench's past year of commit activity - mint-brand Public
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Multimodal-Intelligence-Lab/mint-brand's past year of commit activity - CLIP-CC Public
CLIP-CC: 200 human-narrated descriptions of ~90-second movie clips for long-form video-description research (EvalMG @ SIGIR 2026).
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Multimodal-Intelligence-Lab/CLIP-CC's past year of commit activity - Video-Comprehension-Score Public
VCS is a Python library specifically designed to overcome these challenges by evaluating narrative comprehension through direct comparison of extensive, detailed video descriptions generated by LVLMs against human-written references. Unlike traditional metrics, VCS assesses whether models capture the overall narrative structure, event sequencing, a
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Multimodal-Intelligence-Lab/MuSDeT's past year of commit activity
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