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pro vyhledávání: '"Gohil, Pratham"'
The accurate prediction of danger levels in video content is critical for enhancing safety and security systems, particularly in environments where quick and reliable assessments are essential. In this study, we perform a comparative analysis of vari
Externí odkaz:
http://arxiv.org/abs/2410.19642
Autor:
Gupta, Pranav, Krishnan, Advith, Nanda, Naman, Eswar, Ananth, Agarwal, Deeksha, Gohil, Pratham, Goel, Pratyush
We present a novel dataset aimed at advancing danger analysis and assessment by addressing the challenge of quantifying danger in video content and identifying how human-like a Large Language Model (LLM) evaluator is for the same. This is achieved by
Externí odkaz:
http://arxiv.org/abs/2410.00477