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The Shape of Learning: Anisotropy and Intrinsic Dimensions in
  Transformer-Based Models

The Shape of Learning: Anisotropy and Intrinsic Dimensions in Transformer-Based Models

10 November 2023
Anton Razzhigaev
Matvey Mikhalchuk
Elizaveta Goncharova
Ivan Oseledets
Denis Dimitrov
Andrey Kuznetsov
ArXivPDFHTML

Papers citing "The Shape of Learning: Anisotropy and Intrinsic Dimensions in Transformer-Based Models"

6 / 6 papers shown
Title
Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights
Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights
Zhaiming Shen
Alex Havrilla
Rongjie Lai
A. Cloninger
Wenjing Liao
39
0
0
06 May 2025
The Geometry of Tokens in Internal Representations of Large Language Models
The Geometry of Tokens in Internal Representations of Large Language Models
Karthik Viswanathan
Yuri Gardinazzi
Giada Panerai
Alberto Cazzaniga
Matteo Biagetti
AIFin
94
4
0
17 Jan 2025
Understanding Scaling Laws with Statistical and Approximation Theory for
  Transformer Neural Networks on Intrinsically Low-dimensional Data
Understanding Scaling Laws with Statistical and Approximation Theory for Transformer Neural Networks on Intrinsically Low-dimensional Data
Alex Havrilla
Wenjing Liao
36
8
0
11 Nov 2024
Whitening Consistently Improves Self-Supervised Learning
Whitening Consistently Improves Self-Supervised Learning
András Kalapos
Bálint Gyires-Tóth
SSL
45
0
0
14 Aug 2024
Your Transformer is Secretly Linear
Your Transformer is Secretly Linear
Anton Razzhigaev
Matvey Mikhalchuk
Elizaveta Goncharova
Nikolai Gerasimenko
Ivan Oseledets
Denis Dimitrov
Andrey Kuznetsov
40
4
0
19 May 2024
Efficient Estimation of Word Representations in Vector Space
Efficient Estimation of Word Representations in Vector Space
Tomáš Mikolov
Kai Chen
G. Corrado
J. Dean
3DV
281
31,267
0
16 Jan 2013
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