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

10 November 2023

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 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 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 Alex Havrilla Wenjing Liao 34 8 0 11 Nov 2024
Whitening Consistently Improves Self-Supervised Learning András Kalapos Bálint Gyires-Tóth SSL 45 0 0 14 Aug 2024
Your Transformer is Secretly Linear Anton Razzhigaev Matvey Mikhalchuk Elizaveta Goncharova Nikolai Gerasimenko Ivan V. Oseledets Denis Dimitrov Andrey Kuznetsov 34 4 0 19 May 2024
Efficient Estimation of Word Representations in Vector Space Tomáš Mikolov Kai Chen G. Corrado J. Dean 3DV 266 31,267 0 16 Jan 2013