Prompt Space Optimizing Few-shot Reasoning Success with Large Language Models

arXiv:2306.03799v2 Announce Type: replace
Abstract: Prompt engineering is an essential technique for enhancing the abilities of large language models (LLMs) by providing explicit and specific instructions. It enables LLMs to excel in various tasks, such as arithmetic reasoning, question answering, summarization, relation extraction, machine translation, and sentiment analysis. Researchers have been actively exploring different prompt engineering strategies, such as Chain of Thought (CoT), Zero-CoT, and In-context learning. However, an unresolved problem arises from the fact that current approaches lack a …

arxiv cs.cl few-shot language language models large language large language models prompt reasoning space success type