Demystifying AI: bridging the explainability gap in LLMs

• المؤلف الرئيسي: Chan, Darren Inn Siew
• مؤلفون آخرون: Erik Cambria
• التنسيق: Final Year Project
• اللغة: English
• منشور في: Nanyang Technological University 2024
• الموضوعات: Computer and Information Science; Retrieval augmented generation; Large language models; Explainability of AI; RAG; LLM; XAI; Sustainability reports auditing; Explainable AI
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/175340

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 (...