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From Questions to Insightful Answers: Building an Informed Chatbot for University Resources
This paper presents BARKPLUG V. 2, a Large Language Model (LLM)-based chatbot system built using Retrieval Augmented Generation (RAG) pipelines to enhance the user experience and access to information within academic settings. The objective of BARKPLUG V. 2 is to provide information to users about various campus resources, including academic departments, programs, campus facilities, and student resources at a university setting in an interactive fashion.
MedInsight: A Multi-Source Context Augmentation Framework for Generating Patient-Centric Medical Responses using Large Language Models
Large Language Models (LLMs) have shown impressive capabilities in generating human-like responses.
Advancing Generative Model Evaluation: A Novel Algorithm for Realistic Image Synthesis and Comparison in OCR System
This research addresses a critical challenge in the field of generative models, particularly in the generation and evaluation of synthetic images.
Patient-Centric Knowledge Graphs: A Survey of Current Methods, Challenges, and Applications
Patient-Centric Knowledge Graphs (PCKGs) represent an important shift in healthcare that focuses on individualized patient care by mapping the patient's health information in a holistic and multi-dimensional way.
