Large Language Models (LLMs) are engineered to handle a diverse array of user inputs, known as prompts, which direct the model to generate text, answer questions, or execute tasks. However, specific prompts—often termed "sick prompts"—can disrupt an LLM’s performance, resulting in suboptimal outputs. The quality of an LLM’s responses heavily relies on robust annotation and... Continue Reading →