What are some ways to avoid common methological pitfalls when generating test cases for "groundedness" benchmarks with automation?
Confirmation bias is one obvious pitfall that comes to mind, but also I wonder how it is possible to achieve reproducibility when the input is stochastic.
Confirmation bias is one obvious pitfall that comes to mind, but also I wonder how it is possible to achieve reproducibility when the input is stochastic.