About this document
Prompt Engineering for LLM Sentiment Analysis by hnseccorelinghai is a document available to read on EtoBox.
The document discusses prompt engineering techniques for instruction-tuned large language models (LLMs), focusing on sentiment analysis of course feedback. It also explores the concepts of memorization in LLMs, including discoverable and extractable memorization, and outlines various types of attacks that can be performed on LLM systems, such as membership inference and data extraction attacks. The authors emphasize the implications of these attacks on the privacy and security of training data used in LLMs.
- Author
- hnseccorelinghai
- Language
- EN