Master Key Hypothesis lands NeurIPS 2026 Spotlight: training-free cross-model capability transfer
tuvllms · x · 2026-09-25
The paper "The Master Key Hypothesis" was accepted at NeurIPS 2026 as a Spotlight (top 1.3%: 292 spotlights + 112 orals out of 30,709 submissions).
The proposed UNLOCK framework skips expensive per-model post-training by transferring capabilities directly:
- Skills like CoT and math reasoning live as directions in a model's latent space, captured as a steering vector called the "Master Key"
- Simple low-rank linear transformations suffice to transfer the Master Key across models' latent spaces
- UNLOCK is training-free and label-free, eliciting behaviors that even prompting can't reliably trigger
- Gains scale with base model strength
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