Evaluating Language Model Outputs Using the E-Valgen Framework

Exploring the EvalGen workflow for evaluating language model outputs, including criteria inference, manual selection, and grading options. Emphasizing the importance of tailoring evaluations to individual needs, refining assertions iteratively, and involving human feedback in the assessment loop. Discussing challenges in defining assertions, customizing metrics, and using LOM judges for production environment assessment.