Build your own decision model
Summary
The article discusses building constrained outputs for language models by masking options to force the model to choose among a fixed set of responses. It covers using calibration techniques like temperature scaling to align predicted confidence with accuracy, demonstrates with a Qwen model, and shares evaluation results on CommonsenseQA, plus a GitHub workflow for building and calibrating models.