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DTSTART;VALUE=DATE:20241125
DTEND;VALUE=DATE:20241129
DTSTAMP:20260416T030617
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SUMMARY:BMVC 2024_The 35th British Machine Vision Conference
DESCRIPTION:Davide Caffagni (University of Modena and Reggio Emilia) participated in the 35th British Machine Vision Conference (BMVC)\, presenting the paper “Revisiting Image Captioning Training Paradigm via Direct CLIP-based Optimization”\, co-authored with Nicholas Moratelli\, Marcella Cornia\, Lorenzo Baraldi\, and Rita Cucchiara (University of Modena and Reggio Emilia). \nThe paper introduces Direct CLIP-Based Optimization (DiCO)\, a novel training paradigm for image captioning that improves stability and enhances caption quality by optimizing modern metrics like CLIP-Score while maintaining fluency. The proposed approach outperforms existing methods in aligning with human preferences and generates more informative captions.
URL:https://www.itserr.it/event/bmvc-2024_the-35th-british-machine-vision-conference/
LOCATION:Glasgow\, United Kingdom
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DTSTART;VALUE=DATE:20241126
DTEND;VALUE=DATE:20241130
DTSTAMP:20260416T030617
CREATED:20250319T125201Z
LAST-MODIFIED:20250328T080409Z
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SUMMARY:The 2nd International Conference on Foundation and Large Language Models (FLLM2024)
DESCRIPTION:At FLLM 2024\, Amina El Ganadi (University of Palermo) presented the paper The Impact of Generative AI on Islamic Studies: Case Analysis of “Digital Muhammad ibn Ismail Al-Bukhari”\, co-authored by Sania Aftar\, Luca Gagliardelli\, Sonia Bergamaschi\, and Federico Ruozzi (University of Modena and Reggio Emilia). \nThe study explores the role of generative AI in Islamic studies\, focusing on the Digital Al-Bukhari project and its implications for research and analysis. It examines how large language models can assist in processing and interpreting historical Islamic texts\, offering new tools for scholars.
URL:https://www.itserr.it/event/the-2nd-international-conference-on-foundation-and-large-language-models-fllm2024/
LOCATION:Dubai
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