title: Knowledge Mechanisms in Large Language Models: A Survey and Perspective
summary: Understanding knowledge mechanisms in Large Language Models (LLMs) is crucial
  for advancing towards trustworthy AGI. This paper reviews knowledge mechanism
  analysis from a novel taxonomy including knowledge utilization and evolution.
  Knowledge utilization delves into the mechanism of memorization, comprehension
  and application, and creation. Knowledge evolution focuses on the dynamic
  progression of knowledge within individual and group LLMs. Moreover, we discuss
  what knowledge LLMs have learned, the reasons for the fragility of parametric
  knowledge, and the potential dark knowledge (hypothesis) that will be
  challenging to address. We hope this work can help understand knowledge in LLMs
  and provide insights for future research.
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paper_title: Knowledge Mechanisms in Large Language Models: A Survey and Perspective
paper_summary: Understanding knowledge mechanisms in Large Language Models (LLMs) is crucial
  for advancing towards trustworthy AGI. This paper reviews knowledge mechanism
  analysis from a novel taxonomy including knowledge utilization and evolution.
  Knowledge utilization delves into the mechanism of memorization, comprehension
  and application, and creation. Knowledge evolution focuses on the dynamic
  progression of knowledge within individual and group LLMs. Moreover, we discuss
  what knowledge LLMs have learned, the reasons for the fragility of parametric
  knowledge, and the potential dark knowledge (hypothesis) that will be
  challenging to address. We hope this work can help understand knowledge in LLMs
  and provide insights for future research.
paper_ai_keywords: Large Language Models (LLMs) trustworthy AGI knowledge utilization memorization comprehension application creation knowledge evolution dynamic progression parametric knowledge dark knowledge