UNI ASSIST-AI: An Intelligent University Assistant Chatbot with LLM, RAG, and Multimodal Capabilities
Year: 2026
Type: conference-paper
Abstract: University support systems are under increasing pressure to handle high volumes of student queries accurately and at scale. This paper presents UNI ASSIST-AI, a Retrieval-Augmented Generation (RAG)-based intelligent university assistant that grounds every generated response in verified institutional knowledge. The system integrates a semantic vector retrieval pipeline with a GPT-based generative model, and extends it with multimodal input capabilities—supporting text, voice (via ASR), and image (via OCR) queries. Experimental evaluation yields a Precision of 0.87, Recall of 0.84, and F1-score of 0.85, outperforming both rule-based and vanilla LLM baselines.
Author: ATTREY, DHRUV
Institution: Parul University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7154179435
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