Evaluating Hallucinations in LLMs like GPT4

Some examples of hallucinations in LLM-generated outputs:


Factual Inaccuracies: The LLM produces a statement that is factually incorrect.

Unsupported Claims: The LLM generates a response that has no basis in the input or context.

Nonsensical Statements: The LLM produces a response that doesn’t make sense or is unrelated to the context.

Improbable Scenarios: The LLM generates a response that describes an implausible or highly unlikely event. 

Ref: Detailed article : Mathematically Evaluating Hallucinations in LLMs like GPT4

https://medium.com/autonomous-agents/mathematically-evaluating-hallucinations-in-llms-like-chatgpt-e9db339b39c2

Comments

Popular posts from this blog

Platforms for building and deploying conversational AI agents

Better prompts to harness capability of cgpt

Which AI is suitable for you - Gemini, microsoft copilot, deep seek or claude?