The original title is "Exploring self-distilled reasoning for supervised fine-tuning with Amazon Nova"

Short summary

AWS introduces Self-Distilled Reasoning (SDR), a method for generating thinking tokens in SFT datasets that lack reasoning traces. The post examines the reasoning suppression problem, validates SDR across three benchmarks, and offers practical recommendations for practitioners fine-tuning Amazon Nova models.

• •SDR generates thinking tokens for datasets lacking reasoning traces
• •Addresses reasoning suppression in supervised fine-tuning
• •Validated across three benchmarks with practical recommendations

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