167 citations · 268 across the 15 of their papers we have counts for
4 papers · 1 filter
The Transient Nature of Emergent In-Context Learning in Transformers
Aaditya K. Singh, Stephanie C. Y. Chan, Ted Moskovitz +3
Transformer neural networks can exhibit a surprising capacity for in-context learning (ICL) despite not being explicitly trained for it. Prior work has provided a deeper understand…
Bayes in the age of intelligent machines
Thomas L. Griffiths, Jian-Qiao Zhu, Erin Grant +1
The success of methods based on artificial neural networks in creating intelligent machines seems like it might pose a challenge to explanations of human cognition in terms of Baye…
Getting aligned on representational alignment
Ilia Sucholutsky, Lukas Muttenthaler, Adrian Weller +30
Biological and artificial information processing systems form representations of the world that they can use to categorize, reason, plan, navigate, and make decisions. How can we m…
Statistical physics, Bayesian inference and neural information processing
Erin Grant, Sandra Nestler, Berfin Şimşek +1
Lecture notes from the course given by Professor Sara A. Solla at the Les Houches summer school on "Statistical physics of Machine Learning". The notes discuss neural information p…