Tools like Guidance help during text generation by not necessarily improving on the prompt.

A new paper called "Efficient Guided Generation for Large Language Models" does the same but with a cheaper runtime. One can provide a regex with which the model is guided during text generation. This might help with syntax-heavy tasks. E.g NER token lists ([0, 1, 2, 3]), or some inline tagging Alex B-PER is O going O to O Los B-LOC Angeles I-LOC.

The algorithm requires access to the generation task itself. This would therefore only work with self-hosted models.