SSD: Self-Distillation for Code Generation Without a Teacher

from Mastering Language Models: From Architecture to Optimization

A post-training efficiency episode on simple self-distillation: using a model’s own sampled code outputs as supervised fine-tuning data without a verifier, teacher, or reinforcement learning.

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Frequently Asked Questions

How long is this episode of Mastering Language Models: From Architecture to Optimization?

This episode is 11 minutes long.

When was this Mastering Language Models: From Architecture to Optimization episode published?

This episode was published on April 26, 2026.

What is this episode about?

A post-training efficiency episode on simple self-distillation: using a model’s own sampled code outputs as supervised fine-tuning data without a verifier, teacher, or reinforcement learning.

Can I download this Mastering Language Models: From Architecture to Optimization episode?

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