Bianca Raimondi
• Andrea Gurioli
abstract
This literature review delves into the concept of explainability in the context of large language models (LLMs). It investigates the trade-offs between performance and explainability that are inherent in these models, comparing different approaches and methodologies for enhancing transparency. The review’s goal is to summarize current research, pinpoint gaps, and suggest directions for future work to enhance the explainability of LLMs while preserving their performance.
outcomes
