arxiv
PublishedOctober 13, 2026 at 4:00 AM
REDaCT: Collapse-Free Unlearning in Large Reasoning Models
Publisher summary· verbatim
arXiv:2610.12769v1 Announce Type: cross Abstract: Unlearning in large reasoning models (LRMs) requires removing forget-set information from both the reasoning trace and the final answer. Existing approaches achieve this objective at the cost of reasoning collapse, where the model fails to produce a
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Originally published on arxiv ↗