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Pre-hoc performance prediction can significantly reduce the costs of fine-tuning LLMs by revealing fundamental limits on uncertainty decay.
TUNEAHEAD can predict fine-tuning performance with remarkable accuracy, potentially saving researchers from costly and ineffective training runs.
Forget slow, bloated LLMs – this work shows you can get GPT-4o quality on long-document QA with a 3B model and a clever structure-first distillation approach.
