Pytest for LLM Apps is finally here!DeepEval turns LLM evals into a two-line test suite to help you identify the best models, prompts, and architecture for AI workflows (including MCPs).Learn the limitations of G-Eval and an alternative to it in the explainer below: https://t.co/2d0KUIsILpAvi Chawla (@_avichawla):Most LLM-powered evals are BROKEN!These evals can easily mislead you to believe that one model is better than the other, primarily due to the way they are set up.G-Eval is one popular example.Here' ...

If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):Most LLM-powered evals are BROKEN!These evals can easily mislead you to believe that one model is better than the other, primarily due to the way they are set up.G-Eval is one popular example.Here's the core problem with LLM eval techniques and a better alternative to them: https://t.co/izhjUEEipI ...

Most LLM-powered evals are BROKEN!These evals can easily mislead you to believe that one model is better than the other, primarily due to the way they are set up.G-Eval is one popular example.Here's the core problem with LLM eval techniques and a better alternative to them:Typical evals like G-Eval assume you’re scoring one output at a time in isolation, without understanding the alternative.So when prompt A scores 0.72 and prompt B scores 0.74, you still don’t know which one’s actually better.This is unlik ...