13 citations · 18 across the 15 of their papers we have counts for
3 papers · 1 filter
Adapting Linear-Time Architectures for Tabular In-Context Learning
David Schnurr, Felix Sarnthein, Thomas Hofmann +1
Tabular foundation models achieve strong performance by conditioning on labelled examples in context, but softmax attention limits their use on large datasets. Existing linear-time…
Invariant Learning Dynamics of Transformers in Inductive Reasoning Tasks
Tiberiu Musat, Tiago Pimentel, Nicolas Zucchet +1
We present a theoretical framework to explain the emergence of inductive reasoning abilities in Transformer language models. While previous works on Transformer learning dynamics h…
Fast and Geometrically Grounded Lorentz Neural Networks
Robert van der Klis, Ricardo Chávez Torres, Max van Spengler +3
Hyperbolic space is quickly gaining traction as a promising geometry for hierarchical and robust representation learning. A core open challenge is the development of a mathematical…