Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions

22 November 2022

Papers citing "Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions"

10 / 10 papers shown

Title
A distributional simplicity bias in the learning dynamics of transformers Riccardo Rende Federica Gerace A. Laio Sebastian Goldt 68 8 0 17 Feb 2025
Lower Bounds for Chain-of-Thought Reasoning in Hard-Attention Transformers Alireza Amiri Xinting Huang Mark Rofin Michael Hahn LRM 96 0 0 04 Feb 2025
Training Neural Networks as Recognizers of Formal Languages Alexandra Butoi Ghazal Khalighinejad Anej Svete Josef Valvoda Ryan Cotterell Brian DuSell NAI 33 2 0 11 Nov 2024
Neural Redshift: Random Networks are not Random Functions Damien Teney A. Nicolicioiu Valentin Hartmann Ehsan Abbasnejad 89 18 0 04 Mar 2024
Investigating Recurrent Transformers with Dynamic Halt Jishnu Ray Chowdhury Cornelia Caragea 34 1 0 01 Feb 2024
Simplicity bias, algorithmic probability, and the random logistic map B. Hamzi K. Dingle 23 3 0 31 Dec 2023
Do deep neural networks have an inbuilt Occam's razor? Chris Mingard Henry Rees Guillermo Valle Pérez A. Louis UQCV BDL 19 15 0 13 Apr 2023
Neural Networks and the Chomsky Hierarchy Grégoire Delétang Anian Ruoss Jordi Grau-Moya Tim Genewein L. Wenliang ... Chris Cundy Marcus Hutter Shane Legg Joel Veness Pedro A. Ortega UQCV 94 129 0 05 Jul 2022
Sensitivity as a Complexity Measure for Sequence Classification Tasks Michael Hahn Dan Jurafsky Richard Futrell 143 22 0 21 Apr 2021
Memorisation versus Generalisation in Pre-trained Language Models Michael Tänzer Sebastian Ruder Marek Rei 84 50 0 16 Apr 2021