arXiv Machine Learning July 2, 2026 By Tom Saliencro, Maya Lindqvist, Rohan Desai, Priya Nair, Daniel Whitmore

FRAME: Learning the Adaptation Domain with a Mixture of Fractional-Fourier Experts

Read the original on arXiv Machine Learning →

arXiv:2607. 00162v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) reparameterizes weight updates in a fixed basis: low-rank adapters operate in the spatial domain, while a recent line of spectral methods operates in a fixed Fourier domain.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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