Transformers Are Universally Consistent

30 May 2025

Papers citing "Transformers Are Universally Consistent"

9 / 9 papers shown

Title
A Survey of Controllable Text Generation using Transformer-based Pre-trained Language Models Hanqing Zhang Haolin Song Shaoyu Li Ming Zhou Dawei Song 69 219 0 14 Jan 2022
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai ... Matthias Minderer G. Heigold Sylvain Gelly Jakob Uszkoreit N. Houlsby ViT 400 40,217 0 22 Oct 2020
Big Bird: Transformers for Longer Sequences Manzil Zaheer Guru Guruganesh Kumar Avinava Dubey Joshua Ainslie Chris Alberti ... Philip Pham Anirudh Ravula Qifan Wang Li Yang Amr Ahmed VLM 484 2,051 0 28 Jul 2020
Conformer: Convolution-augmented Transformer for Speech Recognition Anmol Gulati James Qin Chung-Cheng Chiu Niki Parmar Yu Zhang ... Wei Han Shibo Wang Zhengdong Zhang Yonghui Wu Ruoming Pang 190 3,082 0 16 May 2020
Longformer: The Long-Document Transformer Iz Beltagy Matthew E. Peters Arman Cohan RALM VLM 95 3,996 0 10 Apr 2020
Axial Attention in Multidimensional Transformers Jonathan Ho Nal Kalchbrenner Dirk Weissenborn Tim Salimans 81 525 0 20 Dec 2019
Universality of Deep Convolutional Neural Networks Ding-Xuan Zhou HAI PINN 238 514 0 28 May 2018
The Expressive Power of Neural Networks: A View from the Width Zhou Lu Hongming Pu Feicheng Wang Zhiqiang Hu Liwei Wang 67 886 0 08 Sep 2017
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 453 129,831 0 12 Jun 2017