Toy Combinatorial Interpretability Models Reveal Lottery Tickets in Early Feature Space
The lottery ticket hypothesis posits that dense networks contain sparse subnetworks, ``winning tickets,'' that, when rewound to their initial weights and retrained in isolation, match the performance of the full model. We ask a more mechanistic question: what internal object does a winning ticket preserve? We work in a combinatorial, clause-structured toy setting that admits an interpretable feature-space representation with well-defined combinatorial distances between features. We show that winning tickets in weight space correspond to precursor locations in feature space that are already near, at initialization, to the final feature-channel codes. Dense SGD resolves these locations thro...
| Authors | Alon Bebchuk, Nir Shavit |
|---|---|
| Primary category | cs.LG |
| Published | 18 May 2026 |
| Last updated at source | 18 May 2026 |
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