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Stack Attention: Improving the Ability of Transformers to Model
  Hierarchical Patterns

Stack Attention: Improving the Ability of Transformers to Model Hierarchical Patterns

3 October 2023
Brian DuSell
David Chiang
ArXivPDFHTML

Papers citing "Stack Attention: Improving the Ability of Transformers to Model Hierarchical Patterns"

6 / 6 papers shown
Title
TRA: Better Length Generalisation with Threshold Relative Attention
TRA: Better Length Generalisation with Threshold Relative Attention
Mattia Opper
Roland Fernandez
P. Smolensky
Jianfeng Gao
39
0
0
29 Mar 2025
Training Neural Networks as Recognizers of Formal Languages
Training Neural Networks as Recognizers of Formal Languages
Alexandra Butoi
Ghazal Khalighinejad
Anej Svete
Josef Valvoda
Ryan Cotterell
Brian DuSell
NAI
36
2
0
11 Nov 2024
Finding path and cycle counting formulae in graphs with Deep Reinforcement Learning
Finding path and cycle counting formulae in graphs with Deep Reinforcement Learning
Jason Piquenot
Maxime Bérar
Pierre Héroux
Jean-Yves Ramel
R. Raveaux
Sébastien Adam
16
0
0
02 Oct 2024
Investigating Recurrent Transformers with Dynamic Halt
Investigating Recurrent Transformers with Dynamic Halt
Jishnu Ray Chowdhury
Cornelia Caragea
34
1
0
01 Feb 2024
The Surprising Computational Power of Nondeterministic Stack RNNs
The Surprising Computational Power of Nondeterministic Stack RNNs
Brian DuSell
David Chiang
LRM
31
4
0
04 Oct 2022
Transformers Generalize Linearly
Transformers Generalize Linearly
Jackson Petty
Robert Frank
AI4CE
208
16
0
24 Sep 2021
1