Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences

Understand

Due to the cumbersome nature of human evaluation and limitations of code-based evaluation, Large Language Models (LLMs) are increasingly being used to assist humans in evaluating LLM outputs.

• Yet LLM-generated evaluators simply inherit all the problems of the LLMs they evaluate, requiring further human validation.
• We present a mixed-initiative approach to ``validate the validators'' -- aligning LLM-generated evaluation functions (be it prompts or code) with human requirements.
• Our interface, EvalGen, provides automated assistance to users in generating evaluation criteria and implementing assertions.