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 Noah’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 🍁 Previously @GatsbyUCL, @NTUsingapore, @AmazonSDE
Yash Mehta
Customer-Transaction-Analysis - This analysis is based on a synthesised transaction dataset containing 3 months worth of transactions for 100 hypothetical customers.

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salabim - discrete event simulation in Python

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This repo contains the official implementations of EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis

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Code for reproducible experiments presented in KSD Aggregated Goodness-of-fit Test.

Code for KSDAgg: a KSD aggregated goodness-of-fit test This GitHub repository contains the code for the reproducible experiments presented in our pape

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Roadmap to becoming a machine learning engineer in 2020

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Data loaders and abstractions for text and NLP

torchtext This repository consists of: torchtext.datasets: The raw text iterators for common NLP datasets torchtext.data: Some basic NLP building bloc

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Discovering Explanatory Sentences in Legal Case Decisions Using Pre-trained Language Models.

Statutory Interpretation Data Set This repository contains the data set created for the following research papers: Savelka, Jaromir, and Kevin D. Ashl

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HW3 ― GAN, ACGAN and UDA

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A Self-Supervised Contrastive Learning Framework for Aspect Detection

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Lipstick ain't enough: Beyond Color-Matching for In-the-Wild Makeup Transfer (CVPR 2021)

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VinAI Research 248 Dec 13, 2022
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This repo contains the implementation of the algorithm proposed in Off-Belief Learning, ICML 2021.

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GeDML is an easy-to-use generalized deep metric learning library

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Code for our CVPR 2021 paper "MetaCam+DSCE"

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A PaddlePaddle implementation of Time Interval Aware Self-Attentive Sequential Recommendation.

TiSASRec.paddle A PaddlePaddle implementation of Time Interval Aware Self-Attentive Sequential Recommendation. Introduction 论文:Time Interval Aware Sel

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Visual Representation Learning with Self-Supervised Attention for Low-Label High-Data Regime Created by Prarthana Bhattacharyya. Disclaimer: This is n

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Official PyTorch implementation of PICCOLO: Point-Cloud Centric Omnidirectional Localization (ICCV 2021)

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