From Understanding to Utilization: A Survey on Explainability for Large Language Models

arXiv:2401.12874v2 Announce Type: replace
Abstract: Explainability for Large Language Models (LLMs) is a critical yet challenging aspect of natural language processing. As LLMs are increasingly integral to diverse applications, their "black-box" nature sparks significant concerns regarding transparency and ethical use. This survey underscores the imperative for increased explainability in LLMs, delving into both the research on explainability and the various methodologies and tasks that utilize an understanding of these models. Our focus is primarily on pre-trained Transformer-based LLMs, such as …

abstract applications arxiv box concerns cs.ai cs.cl diverse diverse applications ethical explainability integral language language models language processing large language large language models llms natural natural language natural language processing nature processing survey transparency type understanding