Why self-attention is Natural for Sequence-to-Sequence Problems? A
Perspective from Symmetries

Why self-attention is Natural for Sequence-to-Sequence Problems? A Perspective from Symmetries

13 October 2022

Chao Ma

Papers citing "Why self-attention is Natural for Sequence-to-Sequence Problems? A Perspective from Symmetries"

6 / 6 papers shown

Title
Your Transformer May Not be as Powerful as You Expect Shengjie Luo Shanda Li Shuxin Zheng Tie-Yan Liu Liwei Wang Di He 52 50 0 26 May 2022
Universal Approximation Under Constraints is Possible with Transformers Anastasis Kratsios Behnoosh Zamanlooy Tianlin Liu Ivan Dokmanić 48 26 0 07 Oct 2021
Learning with invariances in random features and kernel models Song Mei Theodor Misiakiewicz Andrea Montanari OOD 44 89 0 25 Feb 2021
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas J. Guibas 3DH 3DPC 3DV PINN 219 14,047 0 02 Dec 2016
A Decomposable Attention Model for Natural Language Inference Ankur P. Parikh Oscar Täckström Dipanjan Das Jakob Uszkoreit 196 1,363 0 06 Jun 2016
Effective Approaches to Attention-based Neural Machine Translation Thang Luong Hieu H. Pham Christopher D. Manning 214 7,915 0 17 Aug 2015