Instruction Tuning for Large Language Models: A Survey

arXiv:2308.10792v5 Announce Type: replace-cross
Abstract: This paper surveys research works in the quickly advancing field of instruction tuning (IT), a crucial technique to enhance the capabilities and controllability of large language models (LLMs). Instruction tuning refers to the process of further training LLMs on a dataset consisting of \textsc{(instruction, output)} pairs in a supervised fashion, which bridges the gap between the next-word prediction objective of LLMs and the users' objective of having LLMs adhere to human instructions. In this work, …

abstract arxiv capabilities cs.ai cs.cl cs.lg dataset language language models large language large language models llms paper process research survey surveys training training llms type