Morning Edition · Thursday, July 23, 2026Published at 1:46 AM EDT · New York
Supervised fine-tuning narrows the range of moves models make in sequential decisions, a hidden cost of adapting models to downstream tasks.

A controlled study examines how supervised fine-tuning (SFT) affects behavioral diversity in sequential decision-making, documenting what the authors call diversity collapse in game play. Adapting a model to a downstream task with SFT tends…
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