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RAG-Based Academic Document Question Answering System

This project direction focuses on building an AI/ML prototype inspired by the selected research paper. The work can be framed around model selection, inference, visual intelligence, language-model support, or retrieval-based reasoning, depending…

Project Overview This project direction focuses on building an AI/ML prototype inspired by the selected research paper. The work can be framed around model selection, inference, visual intelligence, language-model support, or retrieval-based reasoning, depending on the chosen dataset and implementation scope. The reference paper, 'Retrieval-Augmented Generation for Large Language Models: A Survey', provides the academic base for the topic. Instead of copying the paper abstract directly, this page keeps the same research intent in a safe paraphrased form: the system retrieves relevant document chunks before generating answers, improving factual grounding and reducing unsupported responses. The final student implementation can include dataset preparation, model/API integration, dashboard or app interface, result explanation, and a short documentation-ready workflow.
Research Paper Title Retrieval-Augmented Generation for Large Language Models: A Survey
Research Paper / PDF Link Open Paper / PDF
Year 2023
Project Area Artificial Intelligence & Machine Learning
Project Type Artificial Project
Required Tools / Software Python, Pandas, Scikit-learn, TensorFlow/PyTorch, HuggingFace/OpenAI API optional, Streamlit
Main Features / Working Principle Collect or upload relevant data, preprocess it, apply an AI/ML/LLM/RAG/software workflow, and present the result through a dashboard or application interface for Artificial Intelligence & Machine Learning.
Expected Output A working B.Tech project prototype for Artificial Intelligence & Machine Learning with input, processing, result display, and explanation/report sections.
Possible Add-ons Admin panel, PDF report export, model comparison, source citations, login system, WhatsApp help button, and deployment on cloud/hosting.
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