
International Journal on Science and Technology
E-ISSN: 2229-7677
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Impact Factor: 9.88
A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 16 Issue 2
April-June 2025
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Intelligent Academic Assistant: An Agentic RAG Framework for QA from Notes and Syllabi
Author(s) | Yash Anil Vaykar, Dr. MADHAVI CHAUDAHRI |
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Country | India |
Abstract | This project presents an Intelligent Academic Assistant: An Agentic RAG Framework for QA from Notes and Syllabi designed to provide accurate syllabus-aligned answers using student’s personal notes and curriculum content. The system allows students to ask questions or upload question papers, and it autonomously extracts relevant content, retrieves semantically similar passages, and generates precise answers using a large language model. |
Field | Computer > Artificial Intelligence / Simulation / Virtual Reality |
Published In | Volume 16, Issue 2, April-June 2025 |
Published On | 2025-06-01 |
DOI | https://doi.org/10.71097/IJSAT.v16.i2.5300 |
Short DOI | https://doi.org/g9m29j |
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IJSAT DOI prefix is
10.71097/IJSAT
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