Research paper AI assistant using retrieval augmented generation and multimodal LLM
Abstract
Researchers often face challenges such as the time-consuming process of document review and the complexity of comprehending technical concepts during journal writing. Emerging large language models, such as ChatGPT and Poe, have proven to be valuable tools for streamlining the writing process. However, these models often require payment for extensive usage or document uploads, posing accessibility barriers. This innovation is motivated by the need to simplify research workflows and enhance the understanding of research documents while ensuring these capabilities are accessible to university users without incurring additional costs. The Research Paper AI Assistant is an innovative system designed to revolutionize how researchers interact with and synthesize information from academic papers. Leveraging advanced technologies such as the Large Language Model (LLM) - Gemma 9b, Retrieval-Augmented Generation (RAG), and the Chroma Embedding Multimodal Model, this innovative system features an intuitive chatbot interface. It enables users to upload multiple PDFs and conduct conversational interactions to extract and synthesize complex information. The scope of the system is specifically confined to the context of the uploaded documents, ensuring focused and relevant responses. The system features automatic diagram analysis for detailed insights and a dedicated "Future Work" tab that instantly identifies key problems and future research directions outlined by authors subsequently,…
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