LLMs hit an effective binding limit in text-to-optimization as data complexity grows, but externalizing numeric data via BIND and binding-focused finetuning raises accuracy from 59% to 82%+ and lets small specialists match larger end-to-end models.
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Models Can Model, But Can't Bind: Structured Grounding in Text-to-Optimization
LLMs hit an effective binding limit in text-to-optimization as data complexity grows, but externalizing numeric data via BIND and binding-focused finetuning raises accuracy from 59% to 82%+ and lets small specialists match larger end-to-end models.