One-Layer Transformer Provably Learns Multiclass One-Nearest Neighbor in Context
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Computer Science > Machine Learning
Title:One-Layer Transformer Provably Learns Multiclass One-Nearest Neighbor in Context
Abstract:We extend recent work establishing an equivalence between one-layer transformers and nearest-neighbor classifiers in the binary setting to the multiclass case. By leveraging the simplex encoding, we show that one-layer transformers with an argmax classification head behave identically to a one-nearest-neighbor classifier in the multiclass setting. This closes a gap left by prior work, whose multiclass result relied on a non-standard rounding-based approach rather than the typical argmax head used in practice.
| Subjects: | Machine Learning (cs.LG); Machine Learning (stat.ML) |
| Cite as: | arXiv:2609.01311 [cs.LG] |
| (or arXiv:2609.01311v1 [cs.LG] for this version) | |
| https://doi.org/10.48550/arXiv.2609.01311
arXiv-issued DOI via DataCite (pending registration)
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