CODI compresses explicit CoT into continuous space via self-distillation and is the first implicit method to match explicit CoT performance on GSM8k at GPT-2 scale with 3.1x compression and 28.2% higher accuracy than prior implicit approaches.
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SHRED performs retain-set-free unlearning by selecting lowest-probability tokens as forget positions and applying a single KL self-distillation objective that demotes logits only at those positions.
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SHRED: Retain-Set-Free Unlearning via Self-Distillation with Logit Demotion
SHRED performs retain-set-free unlearning by selecting lowest-probability tokens as forget positions and applying a single KL self-distillation objective that demotes logits only at those positions.