3 citations · 7 across the 15 of their papers we have counts for
3 papers · 1 filter
Steering Autoregressive Music Generation with Recursive Feature Machines
Daniel Zhao, Daniel Beaglehole, Taylor Berg-Kirkpatrick +2
Controllable music generation remains a significant challenge, with existing methods often requiring model retraining or introducing audible artifacts. We introduce MusicRFM, a fra…
xRFM: Accurate, scalable, and interpretable feature learning models for tabular data
Daniel Beaglehole, David Holzmüller, Adityanarayanan Radhakrishnan +1
Inference from tabular data, collections of continuous and categorical variables organized into matrices, is a foundation for modern technology and science. Yet, in contrast to the…
Toward universal steering and monitoring of AI models
Daniel Beaglehole, Adityanarayanan Radhakrishnan, Enric Boix-Adserà +1
Modern AI models contain much of human knowledge, yet understanding of their internal representation of this knowledge remains elusive. Characterizing the structure and properties…