Reassessing LLM Reliability: Can Large Language Models Accurately Detect Hate Speech?

This research explores the limitations of Large Language Models (LLMs) in detecting hate speech, focusing on their ability to evaluate concepts they might not be able to fully annotate. The study likely examines the implications of this disconnect on the reliability of LLMs in crucial applications.

• •LLMs might struggle to accurately detect hate speech when relying on evaluations of concepts they can't annotate.
• •The research likely investigates how this limitation affects the overall reliability of LLMs.
• •The findings will have implications for the deployment of LLMs in applications requiring accurate content moderation.