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LoRA, DPO, Distillation: Post-Training Steps Don't Commute

This story is from 2026-10-26. It is preserved in the archive; the latest stories are on the live feed.

TL;DR — Teams treat SFT, preference optimization, and distillation as swappable, independently-testable modules in a post-training pipeline. They aren't. The order you apply them changes the final model in ways that per-step evaluation never catches, because LoRA weight deltas, preference gradients…

Read the full story at DEV Community — AI ↗

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  1. 2026-10-26 13:15 · DEV Community — AI
    LoRA, DPO, Distillation: Post-Training Steps Don't Commute

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