Hint-enhanced In-Context Learning wakes Large Language Models up for knowledge-intensive tasks

arXiv:2311.01949v2 Announce Type: replace
Abstract: In-context learning (ICL) ability has emerged with the increasing scale of large language models (LLMs), enabling them to learn input-label mappings from demonstrations and perform well on downstream tasks. However, under the standard ICL setting, LLMs may sometimes neglect query-related information in demonstrations, leading to incorrect predictions. To address this limitation, we propose a new paradigm called Hint-enhanced In-Context Learning (HICL) to explore the power of ICL in open-domain question answering, an important form in …

abstract arxiv context cs.cl enabling however in-context learning information knowledge language language models large language large language models learn llms query scale standard tasks them type