Evaluation of Orca 2 against other LLMs for Retrieval Augmented Generation

• Main Authors: HUANG, Donghao, WANG, Zhaoxia
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Large Language Model (LLM); Generated Pre-trained Transformer (GPT); Retrieval Augmented Generation (RAG); Question Answering; Model Comparison; Artificial Intelligence and Robotics; Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/9052; https://ink.library.smu.edu.sg/context/sis_research/article/10055/viewcontent/RAFDA_2024_Empirical_Evaluation_of_Orca_2_Models_for_Retrieval_Augmented_Generation.pdf
• Institution: Singapore Management University

This study presents a comprehensive evaluation of Microsoft Research’s Orca 2, a small yet potent language model, in the context of Retrieval Augmented Generation (RAG). The research involved comparing Orca 2 with other significant models such as Llama-2, GPT-3.5-Turbo, and GPT-4, particularly focus...