A curated list of awesome resources combining Transformers with Neural Architecture Search

Overview

Awesome Transformer Architecture Search: Awesome

To keep track of the large number of recent papers that look at the intersection of Transformers and Neural Architecture Search (NAS), we have created this awesome list of curated papers and resources, inspired by awesome-autodl, awesome-architecture-search, and awesome-computer-vision. Papers are divided into the following categories:

  1. General Transformer search
  2. Domain Specific, applied Transformer search (divided into NLP, Vision, ASR)
  3. Insights on Transformer components or searchable parameters
  4. Transformer Surveys

This repository is maintained by the AutoML Group Freiburg. Please feel free to pull requests or open an issue to add papers.

General Transformer Search

Title Venue Group
UniNet: Unified Architecture Search with Convolutions, Transformer and MLP arxiv [Oct'21] SenseTime
Analyzing and Mitigating Interference in Neural Architecture Search arxiv [Aug'21] Tsinghua, MSR
BossNAS: Exploring Hybrid CNN-transformers with Block-wisely Self-supervised Neural Architecture Search ICCV'21 Sun Yat-sen University
Memory-Efficient Differentiable Transformer Architecture Search ACL-IJCNLP'21 MSR, Peking University
Finding Fast Transformers: One-Shot Neural Architecture Search by Component Composition arxiv [Aug'20] Google Research
AutoTrans: Automating Transformer Design via Reinforced Architecture Search arxiv [Sep'20] Fudan University
NAT: Neural Architecture Transformer for Accurate and Compact Architectures NeurIPS'19 Tencent AI
The Evolved Transformer ICML'19 Google Brain

Domain Specific Transformer Search

Vision

Title Venue Group
AutoFormer: Searching Transformers for Visual Recognition ICCV'21 MSR
GLiT: Neural Architecture Search for Global and Local Image Transformer ICCV'21 University of Sydney
Searching for Efficient Multi-Stage Vision Transformers ICCV'21 workshop MIT
HR-NAS: Searching Efficient High-Resolution Neural Architectures with Lightweight Transformers CVPR'21 Bytedance Inc.
Vision Transformer Architecture Search arxiv [June'21] SenseTime, Tsingua University

Natural Language Processing

Title Venue Group
AutoTinyBERT: Automatic Hyper-parameter Optimization for Efficient Pre-trained Language Models ACL'21 MIT
NAS-BERT: Task-Agnostic and Adaptive-Size BERT Compression with Neural Architecture Search KDD'21 MSR, Tsinghua University
AutoBERT-Zero: Evolving the BERT backbone from scratch arxiv [July'21] Huawei Noahโ€™s Ark Lab
HAT: Hardware-Aware Transformers for Efficient Natural Language Processing ACL'20 MIT

Automatic Speech Recognition

Title Venue Group
LightSpeech: Lightweight and Fast Text to Speech with Neural Architecture Search ICASSP'21 MSR
Darts-Conformer: Towards Efficient Gradient-Based Neural Architecture Search For End-to-End ASR arxiv [Aug'21] NPU, Xi'an
Improved Conformer-based End-to-End Speech Recognition Using Neural Architecture Search arxiv [April'21] Chinese Academy of Sciences
Evolved Speech-Transformer: Applying Neural Architecture Search to End-to-End Automatic Speech Recognition INTERSPEECH'20 VUNO Inc.

Insights on Transformer components and interesting papers

Title Venue Group
Patches are All You Need ? ICLR'22 under review -
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows ICCV'21 best paper MSR
Rethinking Spatial Dimensions of Vision Transformers ICCV'21 NAVER AI
What makes for hierarchical vision transformers arxiv [Sept'21] HUST
AutoAttend: Automated Attention Representation Search ICML'21 Tsinghua University
Rethinking Attention with Performers ICLR'21 Oral Google
LambdaNetworks: Modeling long-range Interactions without Attention ICLR'21 Google Research
HyperGrid Transformers ICLR'21 Google Research
LocalViT: Bringing Locality to Vision Transformers arxiv [April'21] ETH Zurich
NASABN: A Neural Architecture Search Framework for Attention-Based Networks IJCNN'20 Chinese Academy of Sciences
Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned ACL'19 Yandex

Transformer Surveys

Title Venue Group
Transformers in Vision: A Survey arxiv [Oct'21] MBZ University of AI
Efficient Transformers: A Survey arxiv [Sept'21] Google Research

Misc resources

Owner
Yash Mehta
Researcher, deep learning ๐Ÿ Previously @GatsbyUCL, @NTUsingapore, @AmazonSDE
Yash Mehta
Acute ischemic stroke dataset

AISD Acute ischemic stroke dataset contains 397 Non-Contrast-enhanced CT (NCCT) scans of acute ischemic stroke with the interval from symptom onset to

Kongming Liang 21 Sep 06, 2022
Pytorch-diffusion - A basic PyTorch implementation of 'Denoising Diffusion Probabilistic Models'

PyTorch implementation of 'Denoising Diffusion Probabilistic Models' This reposi

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My freqtrade strategies

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A Peer-to-peer Platform for Secure, Privacy-preserving, Decentralized Data Science

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Get started learning C# with C# notebooks powered by .NET Interactive and VS Code.

.NET Interactive Notebooks for C# Welcome to the home of .NET interactive notebooks for C#! How to Install Download the .NET Coding Pack for VS Code f

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Data and code from COVID-19 machine learning paper

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Create time-series datacubes for supervised machine learning with ICEYE SAR images.

ICEcube is a Python library intended to help organize SAR images and annotations for supervised machine learning applications. The library generates m

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Torchreid: Deep learning person re-identification in PyTorch.

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Detecting Blurred Ground-based Sky/Cloud Images

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Code and project page for ICCV 2021 paper "DisUnknown: Distilling Unknown Factors for Disentanglement Learning"

DisUnknown: Distilling Unknown Factors for Disentanglement Learning See introduction on our project page Requirements PyTorch = 1.8.0 torch.linalg.ei

Sitao Xiang 24 May 16, 2022
Implementation for "Domain-Specific Bias Filtering for Single Labeled Domain Generalization"

DSBF Introduction This repository contains the implementation code for paper: Domain-Specific Bias Filtering for Single Labeled Domain Generalization

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DGCNN - Dynamic Graph CNN for Learning on Point Clouds

DGCNN is the author's re-implementation of Dynamic Graph CNN, which achieves state-of-the-art performance on point-cloud-related high-level tasks including category classification, semantic segmentat

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A framework for analyzing computer vision models with simulated data

3DB: A framework for analyzing computer vision models with simulated data Paper Quickstart guide Blog post Installation Follow instructions on: https:

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Code repo for "RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network" (Machine Learning and the Physical Sciences workshop in NeurIPS 2021).

RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network An official PyTorch implementation of the RBSRICNN network as desc

Rao Muhammad Umer 6 Nov 14, 2022
Fast and robust clustering of point clouds generated with a Velodyne sensor.

Depth Clustering This is a fast and robust algorithm to segment point clouds taken with Velodyne sensor into objects. It works with all available Velo

Photogrammetry & Robotics Bonn 957 Dec 21, 2022
Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras

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๐Ÿฅ‡ LG-AI-Challenge 2022 1์œ„ ์†”๋ฃจ์…˜ ์ž…๋‹ˆ๋‹ค.

LG-AI-Challenge-for-Plant-Classification Dacon์—์„œ ์ง„ํ–‰๋œ ๋†์—… ํ™˜๊ฒฝ ๋ณ€ํ™”์— ๋”ฐ๋ฅธ ์ž‘๋ฌผ ๋ณ‘ํ•ด ์ง„๋‹จ AI ๊ฒฝ์ง„๋Œ€ํšŒ ์— ๋Œ€ํ•œ ์ฝ”๋“œ์ž…๋‹ˆ๋‹ค. (colab directory์— ์ฝ”๋“œ๊ฐ€ ์ž˜ ์ •๋ฆฌ ๋˜์–ด์žˆ์Šต๋‹ˆ๋‹ค.) Requirements python

siwooyong 10 Jun 30, 2022
A Pytorch implementation of MoveNet from Google. Include training code and pre-train model.

Movenet.Pytorch Intro MoveNet is an ultra fast and accurate model that detects 17 keypoints of a body. This is A Pytorch implementation of MoveNet fro

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Dynamic Realtime Animation Control

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HandTailor: Towards High-Precision Monocular 3D Hand Recovery

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