The Role of Feedback Alignment in Self-Distillation
Conditioning a language model on additional context, such as feedback on a previous attempt, typically improves its response. Self-distillation trains the model to retain this improvement when the context is not present. The method works by matching the model's output distribution under two settings: a student that sees only the question, and a self-teacher that also sees the context. What the model learns therefore depends on what context the self-teacher receives, yet the design of this contex
Record details
Published: 9 June 2026
Source: arXiv
Category: Research
Topics: Safety & alignment · Children & education
Retrieved: 14 July 2026
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ethics.ai (9 June 2026), “The Role of Feedback Alignment in Self-Distillation,” evidence record 1180, https://ethics.ai/record/1180 (originally published by arXiv).
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