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DTSTART:20250330T010000
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DTSTART;VALUE=DATE:20250223
DTEND;VALUE=DATE:20250226
DTSTAMP:20260415T234203
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SUMMARY:ICAART 2025 -17th International Conference on Agents and Artificial Intelligence
DESCRIPTION:Irfan Ali (University of Palermo) and Amina El Ganadi (University of Modena and Reggio Emilia) participated in the 17th International Conference on Agents and Artificial Intelligence\, presenting their research on AI applications in linguistic and textual analysis. \nIrfan Ali introduced ABBIE: Attention-Based BI-Encoders for Predicting Where to Split Compound Sanskrit Words\, a deep learning approach leveraging bi-encoders and multi-head attention to achieve 89.27% accuracy in Sanskrit word segmentation. The study introduces a novel deep learning approach using bi-encoders and multi-head attention to accurately predict valid split locations in Sanskrit compound words. Experimental results show that ABBIE outperforms state-of-the-art methods\, achieving 89.27% accuracy. A new dataset was also developed using resources from the Digital Corpus of Sanskrit (DCS) and the University of Hyderabad (UoH) corpus. \nAmina El Ganadi presented Generative AI for Islamic Texts: The EMAN Framework for Mitigating GPT Hallucinations\, which enhances AI reliability in Islamic studies by integrating verified sources to reduce misinformation. Her research explores the challenges of applying large language models (LLMs) to Islamic studies\, addressing issues such as hallucinations and reference inaccuracies. The proposed EMAN framework enhances model reliability through API-based integration with verified sources like Sahih al-Bukhari. The study highlights how embedding-based methodologies improve accuracy and reduce misinformation in AI-generated religious content.
URL:https://www.itserr.it/event/icaart-2025-17th-international-conference-on-agents-and-artificial-intelligence/
LOCATION:Porto\, Portugal
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