Learning to Generate Instruction Tuning Datasets for Zero-Shot Task Adaptation

Bonito is introduced as a model for conditional task generation, aiming to convert unannotated text into task-specific training datasets for instruction tuning. The approach significantly improves the performance of language models on zero-shot task adaptation in specialized domains.