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Curriculum Learning for Safety Alignment

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arXiv:2605. 26315v1 Announce Type: new Abstract: Direct Preference Optimisation (DPO) is widely used for safety alignment in large language models.

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Authors: Sandeep Kumar, Virginia Smith, Chhavi Yadav
Released: 2026-05-27 (1mo ago)
Topic: Related to current project
Relation to my work: Read next because Curriculum Learning for Safety Alignment overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: code, rect, alignment, line, rate, stage, language, model. Source: arxiv cs.LG (Machine Learning).
arXiv: 2605.26315

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