Demystifying AI: bridging the explainability gap in LLMs

Demystifying AI: bridging the explainability gap in LLMs

This project looks at the exploration of Retrieval-Augmented Generation (RAG) with large language models (LLMs) to try and improve the explainability of AI systems within specialized domains, such as auditing sustainability reports. This project would focus on the development of a Proof of Concept (...

Full description

Bibliographic Details
Main Author: Chan, Darren Inn Siew
Other Authors: Erik Cambria
Format: Final Year Project (FYP)
Language:English
Published: Nanyang Technological University 2024
Subjects:
Computer and Information Science
Retrieval augmented generation
Large language models
Explainability of AI
RAG
LLM
XAI
Sustainability reports auditing
Explainable AI
Online Access:https://hdl.handle.net/10356/175340

Internet

https://hdl.handle.net/10356/175340

Similar Items