| Proj No. | A3028-251 |
| Title | Integrating GraphRAG with Large Language Models for Improved Knowledge Retrieval and Content Generation |
| Summary | This project focuses on combining Graph Retrieval-Augmented Generation (GraphRAG) with Large Language Models (LLMs) to enhance domain-specific knowledge retrieval and content generation. By leveraging the power of graph-based structures, GraphRAG enables more accurate and context-aware retrieval of relevant information, which can be seamlessly integrated into the LLM's generation process. The project will explore how this integration can improve real-time decision-making in specialized fields by providing access to up-to-date, structured knowledge. Additionally, we will investigate how GraphRAG can address common LLM limitations, such as hallucination and outdated knowledge, by grounding generated content in reliable graph data. This research aims to develop a robust framework for utilizing GraphRAG and LLMs to deliver more accurate, relevant, and contextually aware outputs for complex tasks. |
| Supervisor | A/P Chen Lihui (Loc:S1 > S1 B1C > S1 B1C 96, Ext: +65 67904484) |
| Co-Supervisor | - |
| RI Co-Supervisor | - |
| Lab | IEM Workshop (former Software Engineering) (Loc: S2.2-B4-04) |
| Single/Group: | Single |
| Area: | Digital Media Processing and Computer Engineering |
| ISP/RI/SMP/SCP?: |