I have been reading some blog posts about LLM as a judge and was building a small evaluator to evaluate the judge itself .
My method is simple:
The dataset is:
task
rubric
ideal response
negative response
The idea is then to test different models as judges for things like:
repeated-run consistency
position bias
sensitivity to verbosity
accuracy / ability to prefer the better response
Here, “negative response” doesn’t necessarily mean a wrong answer. It can just be a response that is less preferred according to the rubric.
I have an initial version with around 200 lines of code
https://github.com/maylad31/judgeDjudge
But I’m more interested in discussing the idea.
If you have used LLM judges in practice, are there other failure modes or better ways of testing them?
Happy to hear criticism or suggestions or positive things about my method/code.
Top comments (0)