most citedEstablishing Performance Baselines in Fine-Tuning, Retrieval-Augmented Generation and Soft-Prompting for Non-Specialist LLM Users

2 citations · 2 across the 1 of their papers we have counts for

collaborators

1 paper

cs.IR2023★ 2 cited

Establishing Performance Baselines in Fine-Tuning, Retrieval-Augmented Generation and Soft-Prompting for Non-Specialist LLM Users

Jennifer Dodgson, Lin Nanzheng, Julian Peh +5

Research into methods for improving the performance of large language models (LLMs) through fine-tuning, retrieval-augmented generation (RAG) and soft-prompting has tended to focus…