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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
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| Paper Title: | Knowledge Augmentation on Documents Through Retrieval Augmented Generation (ADT-RAG) using Generative AI |
| Authors Name: | Shashank Gurunaga |
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IJRTI_205499
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| Published Paper Id: | IJRTI2507150 |
| Published In: | Volume 10 Issue 7, July-2025 |
| DOI: | |
| Abstract: | A modular, document-centric ADT-RAG framework offers a transformative solution to key limitations in large language models, such as hallucinations and outdated knowledge, which are common challenges in traditional NLP-based approaches. While prior methods primarily rely on techniques like part-of-speech tagging, dependency parsing, or vector space models for processing input, this paper introduces a system that dynamically retrieves and integrates knowledge from large-scale, heterogeneous document sources, including PDFs, DOCX, PPTX, and XLS files. Unlike static NLP pipelines, our approach combines dense vector embeddings, semantic similarity-based retrieval, and generative language models to enable more accurate, context-aware, and domain-adaptive responses. The system further supports multi-modal inputs (text and audio), multi-document query analysis, and incorporates feedback mechanisms for continuous learning. Experiments on benchmark datasets demonstrate substantial gains in factual consistency, contextual relevance, and retrieval robustness compared to traditional NLP-based methods, particularly in scenarios involving complex, unstructured document collections. |
| Keywords: | Chunking, Large Language Models (LLM), Retrieval-Augmented Generation (RAG), RetrievalChain, Similarity Score, Vector Embeddings, Vector Store |
| Cite Article: | "Knowledge Augmentation on Documents Through Retrieval Augmented Generation (ADT-RAG) using Generative AI", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 7, page no.b343-b361, July-2025, Available :http://www.ijrti.org/papers/IJRTI2507150.pdf |
| Downloads: | 000369 |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2507150
Registration ID:205499
Published In: Volume 10 Issue 7, July-2025
DOI (Digital Object Identifier):
Page No: b343-b361 Country: Bangalore, Karnataka, India Research Area: Computer Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2507150 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2507150 |
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ISSN: 2456-3315
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Journal Starting Year (ESTD) : 2016
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