What Are Transformers in AI

What Are Transformers in AI

Transformer Architecture

Background

Whether GPT, ChatGPT, DALL-E, Whisper, Satablity AI or whatever significant you see in the AI worlds nowdays it is because of Transformer Architecture. Transformers are a type of neural network architecture that have several properties that make them effective for modeling data with long-range dependencies. They generally feature a combination of multi-headed attention mechanisms, residual connections, layer normalization, feedforward connections, and positional embeddings.

Precursors of Transformers were RNN, LSTM, and GRU architecture. Transformers are based on the 2017 research paper “Attention is All You Need”

Initially, Transformers were used for NLP-related tasks. Slowly researchers started exploring the power of the Transformer Architectures and as of 2023 these are used for hundreds of tasks in different AI domains of technologies like:

• Text Models (NLP, NLU, NLG)
• Vision Models (Computer Vision)
• Audio Models (Audio Processing, Classification, Audio Generation)
• Reinforcement (RL) Models
• Time-series Models
• Multimodal: OCR (extract information from scanned documents), video classification, visual QA, table data question answering
• Graph Models

Starting the journey in 2017, as of now (2023) we have approx 200 Transformer based architectures proposed by various researchers for various purposes. Using these architecture and various benchmark datasets thousands of models have been created which give SOTA performance on various tasks. Based on your need you choose which architecture can help you meet your project objective. There are high chances you will get some pre-trained models which you can use without training (Zero-shot) or small finetuning (one-shot or few-shot) efforts. For that you need to explore Huggingface and PaperWithCode

This articles list all the major Transformer related researcher paper, their creators, capability and date of release.

Tasks, which a Transformer can do

Vision Tasks

• Image classification
• Semantic segmentation
• Video classification
• Object detection
• Zero-shot object detection
• Zero-shot image classification
• Depth estimation

Multimodal Tasks

• Image captioning
• Document Question Answering
• Image to Text
• Text to Video
• Document Question Answering
• Visual Question Answering
• Text to Image
• Image to Image
• Image Generation

Audio Tasks

• Audio classification
• Automatic speech recognition
• Audio to Audio
• Text to Speech
• Voice Activity Detection
• Audio Generation

Text Tasks

• Text classification
• Token classification (NER, POS etc)
• Question answering
• Causal language modeling
• Masked language modeling
• Translation
• Summarization
• Multiple choice
• Sentence Similarity
• Table Question Answering
• Fill in the black (Masking Filling)
• Conversation

Frameworks Used for Developing Models using Above Architectures

As of May’2023 following frameworks are used for creating models. Tensorflow and Pytorch are two most popular frameworks. Keras is not part of Tensorflow.

• TensorFlow
• Caffe
• Caffe2
• PyTorch
• MXNet
• Keras
• Chainer
• JAX

Number of Models in Model Repositories

There are many model repositories but the most famous are as below. These model repositories host pre-trained models. You can download these models and use them for your project.

• Huggingface : As of 2-Jul-23 Huggingface has 243,495 models. In May, 2023, Huggingface has 196,000+ models in the repository. As of Sep’2021, there were 10,000 models. You can see the exponential growth in the models in the Huggingface model repository.
• Another model repository tfhub has around 132,000+ models as of May’23. Tfhub hosts tensorflow-based models.
• Keras Moel Zoo hosts around 3500 models.
• Pytorch Model Hub

Summary of 200+ Transformer

Below is the table which summarises these approx 200 transformers.

Note : Name starting with * are not Transformers, most of them are pretransformer age architectures.
Help Needed: If you find any archive paper’s link is incorrect then let me know via hari.prasad@vedavit-ps.com

Sno.	Transformer	Paper Title	Type	Year	Researcher
1.	*AlexNet Paper	ImageNet Classification with Deep Convolutional Neural Networks	CNN	Dec-2012	University of Toronto, Google
2.	*VGG16 Paper	Very Deep Convolutional Networks for Large-Scale Image Recognition	CNN	Sep-2014	University of Oxford
3.	*VGG19 Paper	Very Deep Convolutional Networks for Large-Scale Image Recognition	CNN	Apr-2015	University of Oxford
4.	*ResNet Paper	Deep Residual Learning for Image Recognition	CNN	Dec-2015	Microsoft Research
5.	*InceptionResNet Paper	Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning	CNN	Aug-2016	Google
6.	*ConvNeXt Paper	Convolutional Neural Networks with Alternately Updated Clique	CNN	Dec-2016	Cornell University, Tsinghua University
7.	*DenseNet Paper	Densely Connected Convolutional Networks	CNN	Jan-2017	Cornell University, Tsinghua University
8.	*MobileNetV1 Paper	Efficient Convolutional Neural Networks for Mobile Vision Applications	Autoencoding	Apr-2017	Google Inc.
9.	*Xception Paper	Xception: Deep Learning with Depthwise Separable Convolutions	CNN	Apr-2017	Google
10.	EncoderDecoder Paper	Leveraging Pre-trained Checkpoints for Sequence Generation Tasks	Sequence-to-Sequence	May-2017	Google Research
11.	*MobileNetV2 Paper	Inverted Residuals and Linear Bottlenecks	Autoencoding	Feb-2018	Google Inc.
12.	Data2Vec Paper	A General Framework for Self-supervised Learning in Speech, Vision and Language	Language Model	Mar-2018	Facebook
13.	GPT Paper	Improving Language Understanding by Generative Pre-Training. Auto-regressive model for next token prediction	Autoregressive	Jun-2018	OpenAI
14.	BERT Paper	Pre-training of Deep Bidirectional Transformers for Language Understanding	Autoencoding	Oct-2018	Google
15.	MarianMT Paper	Machine translation models trained using OPUS data	Autoencoding	Oct-2018
16.	BiT Paper	General Visual Representation Learning	Vision Transformer	Jan-2019	Google AI
17.	Transformer-XL Paper	Attentive Language Models Beyond a Fixed-Length Context	Autoregressive	Jan-2019	Google/CMU
18.	XLM Paper	Cross-lingual Language Model Pretraining	BERT-based	Jan-2019	Facebook
19.	CTRL Paper	A Conditional Transformer Language Model for Controllable Generation	Autoencoding	Feb-2019	Salesforce
20.	GPT-2 Paper	Language Models are Unsupervised Multitask Learners	Autoregressive	Feb-2019	OpenAI
21.	Funnel Transformer Paper	Filtering out Sequential Redundancy for Efficient Language Processing	Autoregressive	Apr-2019	CMU/Google Brain
22.	*EfficientNet B0 Paper	EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks	CNN	May-2019	Google Research
23.	ALBERT Paper	A Lite BERT for Self-supervised Learning of Language Representations,	Factorized BERT	May-2019	Google Research and the Toyota Technological Institute at Chicago
24.	EfficientNet Paper	Rethinking Model Scaling for Convolutional Neural Networks	Vision Transformer	May-2019	Google Brain
25.	MobileNetV3 Paper	Searching for MobileNetV3	Autoencoding	May-2019	Google
26.	Nezha Paper	Neural Contextualized Representation for Chinese Language Understanding	Autoencoding	May-2019	Huawei Noah’s Ark Lab
27.	BART Paper	Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension	Sequence-to-Sequence	Jun-2019	Facebook
28.	ERNIE Paper	Enhanced Representation through Knowledge Integration	Autoencoding	Jun-2019	Baidu
29.	ErnieM Paper	Enhanced Multilingual Representation by Aligning Cross-lingual Semantics with Monolingual Corpora	Autoencoding	Jun-2019	Baidu
30.	FlauBERT Paper	Unsupervised Language Model Pre-training for French	Autoencoding	Jun-2019	CNRS
31.	LXMERT Paper	Learning Cross-Modality Encoder Representations from Transformers for Open-Domain Question Answering	Autoencoding	Jun-2019	UNC Chapel Hill
32.	Pegasus Paper	Pre-training with Extracted Gap-sentences for Abstractive Summarization	Autoregressive	Jun-2019	Google
33.	XLNet Paper	Generalized Autoregressive Pretraining for Language Understanding	Autoregressive	Jun-2019	Google/CMU
34.	BioGpt Paper	generative pre-trained transformer for biomedical text generation and mining	Autoregressive	Jul-2019	Microsoft Research AI4Science
35.	Hubert Paper	Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units	Autoencoding	Jul-2019	Facebook
36.	REALM Paper	Retrieval-Augmented Language Model Pre-Training	Hybrid	Jul-2019	Google Research
37.	SpeechToTextTransformer Paper	Fast Speech-to-Text Modeling with fairseq	Hybrid	Jul-2019	Facebook,
38.	XLM-V Paper	Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models	Multilingual	Jul-2019	Meta AI
39.	RoBERTa Paper	A Robustly Optimized BERT Pretraining Approach	BERT-based	Aug-2019	Facebook
40.	GPT Neo Paper	EleutherAI/gpt-neo	Autoregressive	Sep-2019	EleutherAI
41.	CamemBERT Paper	a Tasty French Language Model	Autoencoding	Oct-2019	Inria/Facebook/Sorbonne
42.	DialoGPT Paper	Large-Scale Generative Pre-training for Conversational Response Generation	Autoregressive	Oct-2019	Microsoft Research
43.	DistilBERT Paper	smaller, faster, cheaper and lighter	Autoencoding	Oct-2019	HuggingFace
44.	LiLT Paper	A Simple yet Effective Language-Independent Layout Transformer for Structured Document Understanding	Autoencoding	Oct-2019	South China University of Technology
45.	LUKE Paper	Deep Contextualized Entity Representations with Entity-aware Self-attention	Autoencoding	Oct-2019	Studio Ousia
46.	MobileBERT Paper	a Compact Task-Agnostic BERT for Resource-Limited Devices	Autoencoding	Oct-2019	CMU/Google Brain
47.	MT5 Paper	A massively multilingual pre-trained text-to-text transformer	Autoregressive	Oct-2019	Google AI
48.	RAG Paper	Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks	Hybrid	Oct-2019	Facebook
49.	ConvBERT Paper	Improving BERT with Span-based Dynamic Convolution	Autoencoding	Nov-2019	YituTech
50.	Megatron-GPT2 Paper	Training Multi-Billion Parameter Language Models Using Model Parallelism	Autoregressive	Nov-2019	NVIDIA
51.	PhoBERT Paper	Pre-trained language models for Vietnamese	BERT-based	Nov-2019	VinAI Research
52.	RoBERTa-PreLayerNorm Paper	A Fast, Extensible Toolkit for Sequence Modeling	BERT-based	Nov-2019	Facebook
53.	BERTweet Paper	A pre-trained language model for English Tweets	Autoencoding	Dec-2019	VinAI Research
54.	mBART Paper	Multilingual Denoising Pre-training for Neural Machine Translation	Autoregressive	Dec-2019	Facebook
55.	Megatron-BERT Paper	Training Multi-Billion Parameter Language Models Using Model Parallelism	Autoregressive	Dec-2019	NVIDIA
56.	SpeechToTextTransformer2 Paper	Large-Scale Self- and Semi-Supervised Learning for Speech Translation	Hybrid	Dec-2019	Facebook,
57.	BERT For Sequence Generation Paper	Leveraging Pre-trained Checkpoints for Sequence Generation Tasks	Autoencoding	Feb-2020	Google
58.	ConvNeXT Paper	A ConvNet for the 2020s	Vision Transformer	Mar-2020	Facebook AI
59.	ELECTRA Paper	Pre-training text encoders as discriminators rather than generators	Autoencoding	Apr-2020	Google Research/Stanford University
60.	Longformer Paper	The Long-Document Transformer	Autoregressive	Apr-2020	AllenAI
61.	RegNet Paper	Designing Network Design Space	CNN	Apr-2020	META Platforms
62.	SqueezeBERT Paper	What can computer vision teach NLP about efficient neural networks?	BERT-based	Apr-2020	Berkeley
63.	LayoutLM Paper	Pre-training of Text and Layout for Document Image Understanding	Autoencoding	May-2020	Microsoft Research Asia
64.	MPNet Paper	Masked and Permuted Pre-training for Language Understanding	Autoencoding	May-2020	Microsoft Research
65.	VisualBERT Paper	A Simple and Performant Baseline for Vision and Language	BERT-based	May-2020	UCLA NLP
66.	Conditional DETR Paper	Conditional DETR for Fast Training Convergence	Vision Transformer	Jun-2020	Microsoft Research Asia
67.	GPTBigCode Paper	don’t reach for the stars!	Autoregressive	Jun-2020	BigCode
68.	M-CTC-T Paper	Pseudo-Labeling For Massively Multilingual Speech Recognition	Autoencoding	Jun-2020	Facebook
69.	Pix2Struct Paper	Screenshot Parsing as Pretraining for Visual Language Understanding	Hybrid	Jun-2020	Google
70.	ProphetNet Paper	Predicting Future N-gram for Sequence-to-Sequence Pre-training	Autoregressive	Jun-2020	Microsoft Research
71.	SEW Paper	Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speech Recognition	Vision Transformer (ViT)	Jun-2020	ASAPP
72.	T5 Paper	Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer	Autoregressive	Jun-2020	Google AI
73.	DeBERTa Paper	Decoding-enhanced BERT with Disentangled Attention	Autoencoding	Jul-2020	Microsoft
74.	Informer Paper	Beyond Efficient Transformer for Long Sequence Time-Series Forecasting	Autoencoding	Jul-2020	Beihang University, UC Berkeley, Rutgers University, SEDD Company
75.	LED Paper	The Long-Document Transformer	Autoregressive	Jul-2020	AllenAI
76.	SwitchTransformers Paper	Scaling to Trillion Parameter Models with Simple and Efficient Sparsity	Hybrid	Jul-2020	Google
77.	Whisper Paper	Robust Speech Recognition via Large-Scale Weak Supervision	Autoregressive	Jul-2020	OpenAI
78.	XLM-ProphetNet Paper	Predicting Future N-gram for Sequence-to-Sequence Pre-training	Hybrid	Jul-2020	Microsoft Research
79.	XLM-RoBERTa Paper	Unsupervised Cross-lingual Representation Learning at Scale	BERT-based	Jul-2020	Facebook AI,
80.	Deformable DETR Paper	Deformable Transformers for End-to-End Object Detection	Vision Transformer	Aug-2020	SenseTime Research
81.	FNet Paper	Mixing Tokens with Fourier Transforms	Autoencoding	Aug-2020	Google Research
82.	GPTSAN-japanese Paper	released in the repository tanreinama/GPTSAN	Autoregressive	Aug-2020
83.	SEW-D Paper	Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speech Recognition	Vision Transformer (ViT)	Aug-2020	ASAPP
84.	CPM Paper	A Large-scale Generative Chinese Pre-trained Language Model	Sequence-to-Sequence	Sep-2020	Tsinghua University
85.	GIT Paper	A Generative Image-to-text Transformer for Vision and Language	Autoencoding	Sep-2020	Microsoft Research
86.	LayoutXLM Paper	Multimodal Pre-training for Multilingual Visually-rich Document Understanding	Autoencoding	Sep-2020	Microsoft Research Asia
87.	DETR Paper	End-to-End Object Detection with Transformers	Vision Transformer	Oct-2020	Facebook
88.	GPT NeoX Paper	An Open-Source Autoregressive Language Model	Autoregressive	Oct-2020	EleutherAI
89.	RemBERT Paper	Rethinking embedding coupling in pre-trained language models	BERT-based	Oct-2020	Google Research
90.	RoCBert Paper	Robust Chinese Bert with Multimodal Contrastive Pretraining	BERT-based	Oct-2020	WeChatAI
91.	TAPAS Paper	Weakly Supervised Table Parsing via Pre-training	Hybrid	Oct-2020	Google AI
92.	UPerNet Paper	Unified Perceptual Parsing for Scene Understanding	Vision Transformer (ViT)	Oct-2020	Peking University
93.	Vision Transformer (ViT) Paper	Transformers for Image Recognition at Scale	Vision Transformer (ViT)	Oct-2020	Google AI
94.	Wav2Vec2 Paper	A Framework for Self-Supervised Learning of Speech Representations	Autoregressive	Oct-2020	Facebook AI
95.	PLBart Paper	Unified Pre-training for Program Understanding and Generation	Hybrid	Nov-2020	UCLA NLP
96.	DiT Paper	Self-supervised Pre-training for Document Image Transformer	Vision Transformer	Dec-2020	Microsoft Research
97.	DPR Paper	Dense Passage Retrieval for Open-Domain Question Answering	Sequence-to-Sequence	Dec-2020	Facebook
98.	GLPN Paper	Global-Local Path Networks for Monocular Depth Estimation with Vertical CutDepth	Autoencoding	Dec-2020	KAIST
99.	LeViT Paper	A Vision Transformer in ConvNet’s Clothing for Faster Inference	Autoencoding	Dec-2020	Meta AI
100.	NAT Paper	Neighborhood Attention Transformer	Autoencoding	Dec-2020	SHI Labs
101.	TAPEX Paper	Table Pre-training via Learning a Neural SQL Executor	Hybrid	Dec-2020	Microsoft Research
102.	VideoMAE Paper	Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training	Hybrid	Dec-2020	Multimedia Computing Group, Nanjing University
103.	Wav2Vec2-Conformer Paper	Fast Speech-to-Text Modeling with FAIRSEQ	Autoregressive	Dec-2020	Facebook AI
104.	CLIP Paper	Learning Transferable Visual Models From Natural Language Supervision	Vision-Language Pretraining	Jan-2021	OpenAI
105.	XLS-R Paper	Self-supervised Cross-lingual Speech Representation Learning at Scale	Autoregressive	Jan-2021	Facebook AI
106.	Audio Spectrogram Transformer Paper	Audio Spectrogram Transformer	Audio Transformer	Feb-2021	MIT
107.	M2M100 Paper	Beyond English-Centric Multilingual Machine Translation	Autoregressive	Feb-2021	Facebook
108.	MEGA Paper	Moving Average Equipped Gated Attention	Autoencoding	Feb-2021	Facebook
109.	BEiT Paper	BERT Pre-Training of Image Transformers	Vision Transformer	Mar-2021	Microsoft
110.	BigBird-Pegasus Paper	Transformers for Longer Sequences	Sequence-to-Sequence	Mar-2021	Google Research
111.	BigBird-RoBERTa Paper	Transformers for Longer Sequences	Autoencoding	Mar-2021	Google Research
112.	CLIPSeg Paper	Image Segmentation Using Text and Image Prompts	Vision-Language Pretraining	Mar-2021	University of Göttingen
113.	DPT Paper	Vision Transformers for Dense Prediction	Vision Transformer	Mar-2021	Intel Labs
114.	Perceiver IO Paper	A General Architecture for Structured Inputs & Outputs	Hybrid	Mar-2021	Deepmind
115.	Reformer Paper	The Efficient Transformer	Hybrid	Mar-2021	Google Research
116.	RoFormer Paper	Enhanced Transformer with Rotary Position Embedding	Hybrid	Mar-2021	ZhuiyiTechnology
117.	Swin Transformer Paper	Hierarchical Vision Transformer using Shifted Windows	Vision Transformer (ViT)	Mar-2021	Microsoft
118.	TrOCR Paper	Transformer-based Optical Character Recognition with Pre-trained Models	Hybrid	Mar-2021	Microsoft,
119.	Wav2Vec2Phoneme Paper	Simple and Effective Zero-shot Cross-lingual Phoneme Recognition	Autoregressive	Mar-2021	Facebook AI
120.	X-CLIP Paper	Expanding Language-Image Pretrained Models for General Video Recognition	Hybrid	Mar-2021	Microsoft Research
121.	XLSR-Wav2Vec2 Paper	Unsupervised Cross-Lingual Representation Learning For Speech Recognition	Autoregressive	Mar-2021	Facebook AI
122.	Blenderbot Paper	Recipes for building an open-domain chatbot	Sequence-to-Sequence	Apr-2021	Facebook
123.	BlenderbotSmall Paper	Recipes for building an open-domain chatbot	Sequence-to-Sequence	Apr-2021	Facebook
124.	BLIP Paper	Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation	Vision Transformer	Apr-2021	Salesforce
125.	ByT5 Paper	Towards a token-free future with pre-trained byte-to-byte models	Sequence-to-Sequence	Apr-2021	Google Research
126.	CvT Paper	Introducing Convolutions to Vision Transformers	Vision Transformer	Apr-2021	Microsoft
127.	DeBERTa-v2 Paper	Decoding-enhanced BERT with Disentangled Attention	Autoencoding	Apr-2021	Microsoft
128.	DeiT Paper	Training data-efficient image transformers & distillation through attention	Vision Transformer	Apr-2021	Facebook
129.	GroupViT Paper	Semantic Segmentation Emerges from Text Supervision	Autoencoding	Apr-2021	UCSD, NVIDIA
130.	LayoutLMv2 Paper	Multi-modal Pre-training for Visually-Rich Document Understanding	Autoencoding	Apr-2021	Microsoft Research Asia
131.	MaskFormer Paper	Per-Pixel Classification is Not All You Need for Semantic Segmentation	Autoencoding	Apr-2021	Meta and UIUC
132.	SegFormer Paper	Simple and Efficient Design for Semantic Segmentation with Transformers	Hybrid	Apr-2021	NVIDIA
133.	Time Series Transformer Paper		Hybrid	Apr-2021	HuggingFace.
134.	TimeSformer Paper	Space-Time Attention All You Need for Video Understanding?	Hybrid	Apr-2021	Facebook
135.	Trajectory Transformer Paper	Offline Reinforcement Learning as One Big Sequence Modeling Problem	Hybrid	Apr-2021	the University of California at Berkeley
136.	UniSpeech Paper	Unified Speech Representation Learning with Labeled and Unlabeled Data	Hybrid	Apr-2021	Microsoft Research
137.	UniSpeechSat Paper	UNIVERSAL SPEECH REPRESENTATION LEARNING WITH SPEAKER AWARE PRE-TRAINING	Hybrid	Apr-2021	Microsoft Research
138.	ALIGN Paper	Scaling Up Visual and Vision-Language. Representation Learning With Noisy Text Supervision	Vision Transformer	May-2021	Google Research
139.	BORT Paper	Optimal Subarchitecture Extraction For BERT	Sequence-to-Sequence	May-2021	Alexa
140.	DePlot Paper	One-shot visual language reasoning by plot-to-table translation	Vision Transformer	May-2021	Google AI
141.	DETA Paper	NMS Strikes Back	Sequence-to-Sequence	May-2021	The University of Texas at Austin
142.	DiNAT Paper	Dilated Neighborhood Attention Transformer	Vision Transformer	May-2021	SHI Labs
143.	Jukebox Paper	A Generative Model for Music	Autoencoding	May-2021	OpenAI
144.	mBART-50 Paper	Multilingual Translation with Extensible Multilingual Pretraining and Finetuning	Autoregressive	May-2021	Facebook
145.	Nyströmformer Paper	A Nyström-Based Algorithm for Approximating Self-Attention	Autoencoding	May-2021	the University of Wisconsin - Madison
146.	ViT Hybrid Paper	Transformers for Image Recognition at Scale	Hybrid	May-2021	Google AI
147.	X-MOD Paper	Lifting the Curse of Multilinguality by Pre-training Modular Transformers	Hybrid	May-2021	Meta AI
148.	BARTpho Paper	Pre-trained Sequence-to-Sequence Models for Vietnamese	Autoregressive	Jun-2021	VinAI Research
149.	BridgeTower Paper	Building Bridges Between Encoders in Vision-Language Representation Learning	Vision Transformer	Jun-2021	Harbin Institute of Technology/Microsoft Research Asia/Intel Labs
150.	CodeGen Paper	A Conversational Paradigm for Program Synthesis	Vision Transformer	Jun-2021	Salesforce
151.	GPT-J Paper	released in the repository kingoflolz/mesh-transformer-jax	Autoregressive	Jun-2021	EleutherAI
152.	LLaMA Paper	Open and Efficient Foundation Language Models	Autoencoding	Jun-2021	The FAIR team of Meta AI
153.	MarkupLM Paper	Pre-training of Text and Markup Language for Visually-rich Document Understanding	Autoencoding	Jun-2021	Microsoft Research Asia
154.	PoolFormer Paper	MetaFormer is Actually What You Need for Vision	Autoregressive	Jun-2021	Sea AI Labs
155.	QDQBert Paper	Principles and Empirical Evaluation	BERT-based	Jun-2021	NVIDIA
156.	ViLT Paper	Vision-and-Language Transformer Without Convolution or Region Supervision	Vision Transformer (ViT)	Jun-2021	NAVER AI Lab/Kakao Enterprise/Kakao Brain
157.	BARThez Paper	a Skilled Pretrained French Sequence-to-Sequence Model	Autoregressive	Jul-2021	École polytechnique
158.	Donut Paper	OCR-free Document Understanding Transformer	Time Series Transformer	Jul-2021	NAVER
159.	ImageGPT Paper	Generative Pretraining from Pixels	Autoregressive	Jul-2021	OpenAI
160.	OPT Paper	Open Pre-trained Transformer Language Models	Hybrid	Jul-2021	Meta AI
161.	Splinter Paper	Few-Shot Question Answering by Pretraining Span Selection	Hybrid	Jul-2021	Tel Aviv University,
162.	XGLM Paper	Few-shot Learning with Multilingual Language Models	Hybrid	Jul-2021	Facebook AI
163.	YOSO Paper	You Only Sample (Almost)	Object Detection	Jul-2021	the University of Wisconsin - Madison
164.	EfficientFormer Paper	Vision Transformers at MobileNetSpeed	Vision Transformer	Aug-2021	Snap Research
165.	ESM Paper	ESM-1b. Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences. ESM-1v was released with the paper Language models enable zero-shot prediction of the effects of mutations on protein function. ESM-2 and ESMFold were released with the paper Language models of protein sequences at the scale of evolution enable accurate structure prediction	Protein Transformer	Aug-2021	Meta AI
166.	Mask2Former Paper	Masked-attention Mask Transformer for Universal Image Segmentation	Autoencoding	Aug-2021	FAIR and UIUC
167.	MGP-STR Paper	Multi-Granularity Prediction for Scene Text Recognition	Autoencoding	Aug-2021	Alibaba Research
168.	NLLB Paper	Scaling Human-Centered Machine Translation	Autoencoding	Aug-2021	Meta
169.	T5v1.1 Paper	released in the repository google-research/text-to-text-transfer-transformer	Autoregressive	Aug-2021	Google AI
170.	TVLT Paper	Textless Vision-Language Transformer	Hybrid	Aug-2021	UNC Chapel Hill
171.	WavLM Paper	Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing	Autoregressive	Aug-2021	Microsoft Research
172.	XLM-RoBERTa-XL Paper	Larger-Scale Transformers for Multilingual Masked Language Modeling	BERT-based	Aug-2021	Facebook AI,
173.	Chinese-CLIP Paper	Contrastive Vision-Language Pretraining in Chinese	Vision-Language Pretraining	Sep-2021	OFA-Sys
174.	CLAP Paper	[Large-scale Contrastive Language-Audio Pretraining with Feature Fusion and Keyword-to-Caption Augmentation]https //arxiv.org/abs/2211.06687)	Vision Transformer	Sep-2021	LAION-AI
175.	Decision Transformer Paper	Reinforcement Learning via Sequence Modeling	Vision Transformer	Sep-2021	Berkeley/Facebook/Google
176.	BLIP-2 Paper	Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models	Vision Transformer	Oct-2021	Salesforce
177.	CANINE Paper	Pre-training an Efficient Tokenization-Free Encoder for Language Representation	Vision Transformer	Oct-2021	Google Research
178.	Graphormer Paper	Do Transformers Really Perform Bad for Graph Representation?	Autoencoding	Oct-2021	Microsoft
179.	I-BERT Paper	Integer-only BERT Quantization	Autoencoding	Oct-2021	Berkeley
180.	MatCha Paper	Enhancing Visual Language Pretraining with Math Reasoning and Chart Derendering	Autoencoding	Oct-2021	Google AI
181.	mLUKE Paper	The Power of Entity Representations in Multilingual Pretrained Language Models	Autoencoding	Oct-2021	Studio Ousia
182.	MobileViT Paper	Light-weight, General-purpose, and Mobile-friendly Vision Transformer	Autoencoding	Oct-2021	Apple
183.	OWL-ViT Paper	Simple Open-Vocabulary Object Detection with Vision Transformers	Vision Transformer (ViT)	Oct-2021	Google AI
184.	SpeechT5 Paper	Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing	Autoregressive	Oct-2021	Microsoft Research
185.	Swin Transformer V2 Paper	Scaling Up Capacity and Resolution	Vision Transformer (ViT)	Oct-2021	Microsoft
186.	ViTMAE Paper	Masked Autoencoders Are Scalable Vision Learners	Vision Transformer (ViT)	Oct-2021	Meta AI
187.	BLOOM Paper	The architecture of BLOOM is essentially similar to GPT3, but has been trained on 46 different languages and 13 programming languages.	Vision Transformer	Nov-2021	BigScience workshop
188.	ConvNeXTV2 Paper	Co-designing and Scaling ConvNets with Masked Autoencoders	Vision Transformer	Nov-2021	Facebook AI
189.	CPM-Ant Paper		Sequence-to-Sequence	Nov-2021	OpenBMB
190.	GPT-Sw3 Paper	Building the First Large-Scale Generative Language Model for Swedish	Autoregressive	Nov-2021	AI-Sweden
191.	LongT5 Paper	Efficient Text-To-Text Transformer for Long Sequences	Autoregressive	Nov-2021	Google AI
192.	OneFormer Paper	One Transformer to Rule Universal Image Segmentation	Autoregressive	Nov-2021	SHI Labs
193.	Table Transformer Paper	Towards Comprehensive Table Extraction From Unstructured Documents	Hybrid	Nov-2021	Microsoft Research
194.	VAN Paper	Visual Attention Network	Vision Transformer (ViT)	Nov-2021	Tsinghua University and Nankai University
195.	AltCLIP Paper	Altering the Language Encoder in CLIP for Extended Language Capabilities	Vision-Language Pretraining	Dec-2021	BAAI
196.	MVP Paper	Multi-task Supervised Pre-training for Natural Language Generation	Autoencoding	Dec-2021	RUC AI Box
197.	NLLB-MOE Paper	Scaling Human-Centered Machine Translation	Autoencoding	Dec-2021	Meta
198.	PEGASUS-X Paper	Investigating Efficiently Extending Transformers for Long Input Summarization	Autoregressive	Dec-2021	Google
199.	Swin2SR Paper	SwinV2 Transformer for Compressed Image Super-Resolution and Restoration	Vision Transformer (ViT)	Dec-2021	University of Würzburg
200.	UL2 Paper	Unifying Language Learning Paradigms	Hybrid	Dec-2021	Google Research
201.	ViTMSN Paper	Masked Siamese Networks for Label-Efficient Learning	Vision Transformer (ViT)	Dec-2021	Meta AI
202.	YOLOS Paper	Rethinking Transformer in Vision through Object Detection	Object Detection	Dec-2021	Huazhong University of Science & Technology
203.	FLAN-T5 Paper	released in the repository google-research/t5x	Autoregressive	Feb-2022	Google AI
204.	GPT NeoX Japanese Paper	by Shinya Otani, Takayoshi Makabe, Anuj Arora, and Kyo Hattori.	Autoregressive	Feb-2022	ABEJA
205.	LayoutLMv3 Paper	Pre-training for Document AI with Unified Text and Image Masking	Autoencoding	Mar-2022	Microsoft Research Asia
206.	FLAN-UL2 Paper	released in the repository google-research/t5x	Autoregressive	Apr-2022	Google AI
207.	FLAVA Paper	A Foundational Language And Vision Alignment Model	Autoencoding	Apr-2022	Facebook AI

Authors of Above Papers

Sno.	Paper	Author
1.	*AlexNet Paper	Alex Krizhevsky, Ilya Sutskever, Geoffrey Hinton
2.	*VGG16 Paper	Karen Simonyan, Andrew Zisserman
3.	*VGG19 Paper	Karen Simonyan, Andrew Zisserman
4.	*ResNet Paper	by Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun.
5.	*InceptionResNet Paper	Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, Alex Alemi
6.	*ConvNeXt Paper	Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, Kilian Weinberger
7.	*DenseNet Paper	Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger
8.	*MobileNetV1 Paper	by Andrew G. Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, Hartwig Adam.
9.	*Xception Paper	François Chollet
10.	EncoderDecoder Paper	by Sascha Rothe, Shashi Narayan, Aliaksei Severyn.
11.	*MobileNetV2 Paper	by Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen.
12.	Data2Vec Paper	by Alexei Baevski, Wei-Ning Hsu, Qiantong Xu, Arun Babu, Jiatao Gu, Michael Auli.
13.	GPT Paper	by Alec Radford, Karthik Narasimhan, Tim Salimans and Ilya Sutskever.
14.	BERT Paper	by Jacob Devlin, Ming-Wei Chang, Kenton Lee and Kristina Toutanova.
15.	MarianMT Paper	by Jörg Tiedemann. The Marian Framework is being developed by the Microsoft Translator Team.
16.	BiT Paper	by Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Joan Puigcerver, Jessica Yung, Sylvain Gelly, Neil Houlsby.
17.	Transformer-XL Paper	by Zihang Dai, Zhilin Yang, Yiming Yang, Jaime Carbonell, Quoc V. Le, Ruslan Salakhutdinov.
18.	XLM Paper	by Guillaume Lample and Alexis Conneau.
19.	CTRL Paper	by Nitish Shirish Keskar, Bryan McCann, Lav R. Varshney, Caiming Xiong and Richard Socher.
20.	GPT-2 Paper	by Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodeiand Ilya Sutskever.
21.	Funnel Transformer Paper	by Zihang Dai, Guokun Lai, Yiming Yang, Quoc V. Le.
22.	*EfficientNet B0 Paper	Mingxing Tan, Quoc V. Le
23.	ALBERT Paper	by Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, Radu Soricut.
24.	EfficientNet Paper	by Mingxing Tan, Quoc V. Le.
25.	MobileNetV3 Paper	Andrew Howard, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang, Yukun Zhu, Ruoming Pang, Vijay Vasudevan, Quoc V. Le, Hartwig Adam
26.	Nezha Paper	by Junqiu Wei, Xiaozhe Ren, Xiaoguang Li, Wenyong Huang, Yi Liao, Yasheng Wang, Jiashu Lin, Xin Jiang, Xiao Chen and Qun Liu.
27.	BART Paper	by Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov and Luke Zettlemoyer.
28.	ERNIE Paper	by Yu Sun, Shuohuan Wang, Yukun Li, Shikun Feng, Xuyi Chen, Han Zhang, Xin Tian, Danxiang Zhu, Hao Tian, Hua Wu.
29.	ErnieM Paper	by Xuan Ouyang, Shuohuan Wang, Chao Pang, Yu Sun, Hao Tian, Hua Wu, Haifeng Wang.
30.	FlauBERT Paper	by Hang Le, Loïc Vial, Jibril Frej, Vincent Segonne, Maximin Coavoux, Benjamin Lecouteux, Alexandre Allauzen, Benoît Crabbé, Laurent Besacier, Didier Schwab.
31.	LXMERT Paper	by Hao Tan and Mohit Bansal.
32.	Pegasus Paper	by Jingqing Zhang, Yao Zhao, Mohammad Saleh and Peter J. Liu.
33.	XLNet Paper	by Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Ruslan Salakhutdinov, Quoc V. Le.
34.	BioGpt Paper	by Renqian Luo, Liai Sun, Yingce Xia, Tao Qin, Sheng Zhang, Hoifung Poon and Tie-Yan Liu.
35.	Hubert Paper	by Wei-Ning Hsu, Benjamin Bolte, Yao-Hung Hubert Tsai, Kushal Lakhotia, Ruslan Salakhutdinov, Abdelrahman Mohamed.
36.	REALM Paper	by Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat and Ming-Wei Chang.
37.	SpeechToTextTransformer Paper	by Changhan Wang, Yun Tang, Xutai Ma, Anne Wu, Dmytro Okhonko, Juan Pino.
38.	XLM-V Paper	by Davis Liang, Hila Gonen, Yuning Mao, Rui Hou, Naman Goyal, Marjan Ghazvininejad, Luke Zettlemoyer, Madian Khabsa.
39.	RoBERTa Paper	by Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, Veselin Stoyanov.
40.	GPT Neo Paper	by Sid Black, Stella Biderman, Leo Gao, Phil Wang and Connor Leahy.
41.	CamemBERT Paper	by Louis Martin, Benjamin Muller, Pedro Javier Ortiz Suárez*, Yoann Dupont, Laurent Romary, Éric Villemonte de la Clergerie, Djamé Seddah and Benoît Sagot.
42.	DialoGPT Paper	by Yizhe Zhang, Siqi Sun, Michel Galley, Yen-Chun Chen, Chris Brockett, Xiang Gao, Jianfeng Gao, Jingjing Liu, Bill Dolan.
43.	DistilBERT Paper	by Victor Sanh, Lysandre Debut and Thomas Wolf. The same method has been applied to compress GPT2 into DistilGPT2, RoBERTa into DistilRoBERTa, Multilingual BERT into DistilmBERT and a German version of DistilBERT.
44.	LiLT Paper	by Jiapeng Wang, Lianwen Jin, Kai Ding.
45.	LUKE Paper	by Ikuya Yamada, Akari Asai, Hiroyuki Shindo, Hideaki Takeda, Yuji Matsumoto.
46.	MobileBERT Paper	by Zhiqing Sun, Hongkun Yu, Xiaodan Song, Renjie Liu, Yiming Yang, and Denny Zhou.
47.	MT5 Paper	by Linting Xue, Noah Constant, Adam Roberts, Mihir Kale, Rami Al-Rfou, Aditya Siddhant, Aditya Barua, Colin Raffel.
48.	RAG Paper	by Patrick Lewis, Ethan Perez, Aleksandara Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, Douwe Kiela.
49.	ConvBERT Paper	by Zihang Jiang, Weihao Yu, Daquan Zhou, Yunpeng Chen, Jiashi Feng, Shuicheng Yan.
50.	Megatron-GPT2 Paper	by Mohammad Shoeybi, Mostofa Patwary, Raul Puri, Patrick LeGresley, Jared Casper and Bryan Catanzaro.
51.	PhoBERT Paper	by Dat Quoc Nguyen and Anh Tuan Nguyen.
52.	RoBERTa-PreLayerNorm Paper	by Myle Ott, Sergey Edunov, Alexei Baevski, Angela Fan, Sam Gross, Nathan Ng, David Grangier, Michael Auli.
53.	BERTweet Paper	by Dat Quoc Nguyen, Thanh Vu and Anh Tuan Nguyen.
54.	mBART Paper	by Yinhan Liu, Jiatao Gu, Naman Goyal, Xian Li, Sergey Edunov, Marjan Ghazvininejad, Mike Lewis, Luke Zettlemoyer.
55.	Megatron-BERT Paper	by Mohammad Shoeybi, Mostofa Patwary, Raul Puri, Patrick LeGresley, Jared Casper and Bryan Catanzaro.
56.	SpeechToTextTransformer2 Paper	by Changhan Wang, Anne Wu, Juan Pino, Alexei Baevski, Michael Auli, Alexis Conneau.
57.	BERT For Sequence Generation Paper	by Sascha Rothe, Shashi Narayan, Aliaksei Severyn.
58.	ConvNeXT Paper	by Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, Saining Xie.
59.	ELECTRA Paper	by Kevin Clark, Minh-Thang Luong, Quoc V. Le, Christopher D. Manning.
60.	Longformer Paper	by Iz Beltagy, Matthew E. Peters, Arman Cohan.
61.	RegNet Paper	by Ilija Radosavovic, Raj Prateek Kosaraju, Ross Girshick, Kaiming He, Piotr Dollár.
62.	SqueezeBERT Paper	by Forrest N. Iandola, Albert E. Shaw, Ravi Krishna, and Kurt W. Keutzer.
63.	LayoutLM Paper	by Yiheng Xu, Minghao Li, Lei Cui, Shaohan Huang, Furu Wei, Ming Zhou.
64.	MPNet Paper	by Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, Tie-Yan Liu.
65.	VisualBERT Paper	by Liunian Harold Li, Mark Yatskar, Da Yin, Cho-Jui Hsieh, Kai-Wei Chang.
66.	Conditional DETR Paper	by Depu Meng, Xiaokang Chen, Zejia Fan, Gang Zeng, Houqiang Li, Yuhui Yuan, Lei Sun, Jingdong Wang.
67.	GPTBigCode Paper	by Loubna Ben Allal, Raymond Li, Denis Kocetkov, Chenghao Mou, Christopher Akiki, Carlos Munoz Ferrandis, Niklas Muennighoff, Mayank Mishra, Alex Gu, Manan Dey, Logesh Kumar Umapathi, Carolyn Jane Anderson, Yangtian Zi, Joel Lamy Poirier, Hailey Schoelkopf, Sergey Troshin, Dmitry Abulkhanov, Manuel Romero, Michael Lappert, Francesco De Toni, Bernardo García del Río, Qian Liu, Shamik Bose, Urvashi Bhattacharyya, Terry Yue Zhuo, Ian Yu, Paulo Villegas, Marco Zocca, Sourab Mangrulkar, David Lansky, Huu Nguyen, Danish Contractor, Luis Villa, Jia Li, Dzmitry Bahdanau, Yacine Jernite, Sean Hughes, Daniel Fried, Arjun Guha, Harm de Vries, Leandro von Werra.
68.	M-CTC-T Paper	by Loren Lugosch, Tatiana Likhomanenko, Gabriel Synnaeve, and Ronan Collobert.
69.	Pix2Struct Paper	by Kenton Lee, Mandar Joshi, Iulia Turc, Hexiang Hu, Fangyu Liu, Julian Eisenschlos, Urvashi Khandelwal, Peter Shaw, Ming-Wei Chang, Kristina Toutanova.
70.	ProphetNet Paper	by Yu Yan, Weizhen Qi, Yeyun Gong, Dayiheng Liu, Nan Duan, Jiusheng Chen, Ruofei Zhang and Ming Zhou.
71.	SEW Paper	by Felix Wu, Kwangyoun Kim, Jing Pan, Kyu Han, Kilian Q. Weinberger, Yoav Artzi.
72.	T5 Paper	by Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu.
73.	DeBERTa Paper	by Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen.
74.	Informer Paper	by Haoyi Zhou, Shanghang Zhang, Jieqi Peng, Shuai Zhang, Jianxin Li, Hui Xiong, and Wancai Zhang.
75.	LED Paper	by Iz Beltagy, Matthew E. Peters, Arman Cohan.
76.	SwitchTransformers Paper	by William Fedus, Barret Zoph, Noam Shazeer.
77.	Whisper Paper	by Alec Radford, Jong Wook Kim, Tao Xu, Greg Brockman, Christine McLeavey, Ilya Sutskever.
78.	XLM-ProphetNet Paper	by Yu Yan, Weizhen Qi, Yeyun Gong, Dayiheng Liu, Nan Duan, Jiusheng Chen, Ruofei Zhang and Ming Zhou.
79.	XLM-RoBERTa Paper	by Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer and Veselin Stoyanov.
80.	Deformable DETR Paper	by Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, Jifeng Dai.
81.	FNet Paper	by James Lee-Thorp, Joshua Ainslie, Ilya Eckstein, Santiago Ontanon.
82.	GPTSAN-japanese Paper	by Toshiyuki Sakamoto(tanreinama).
83.	SEW-D Paper	by Felix Wu, Kwangyoun Kim, Jing Pan, Kyu Han, Kilian Q. Weinberger, Yoav Artzi.
84.	CPM Paper	by Zhengyan Zhang, Xu Han, Hao Zhou, Pei Ke, Yuxian Gu, Deming Ye, Yujia Qin, Yusheng Su, Haozhe Ji, Jian Guan, Fanchao Qi, Xiaozhi Wang, Yanan Zheng, Guoyang Zeng, Huanqi Cao, Shengqi Chen, Daixuan Li, Zhenbo Sun, Zhiyuan Liu, Minlie Huang, Wentao Han, Jie Tang, Juanzi Li, Xiaoyan Zhu, Maosong Sun.
85.	GIT Paper	by Jianfeng Wang, Zhengyuan Yang, Xiaowei Hu, Linjie Li, Kevin Lin, Zhe Gan, Zicheng Liu, Ce Liu, Lijuan Wang.
86.	LayoutXLM Paper	by Yiheng Xu, Tengchao Lv, Lei Cui, Guoxin Wang, Yijuan Lu, Dinei Florencio, Cha Zhang, Furu Wei.
87.	DETR Paper	by Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, Sergey Zagoruyko.
88.	GPT NeoX Paper	by Sid Black, Stella Biderman, Eric Hallahan, Quentin Anthony, Leo Gao, Laurence Golding, Horace He, Connor Leahy, Kyle McDonell, Jason Phang, Michael Pieler, USVSN Sai Prashanth, Shivanshu Purohit, Laria Reynolds, Jonathan Tow, Ben Wang, Samuel Weinbach
89.	RemBERT Paper	by Hyung Won Chung, Thibault Févry, Henry Tsai, M. Johnson, Sebastian Ruder.
90.	RoCBert Paper	by HuiSu, WeiweiShi, XiaoyuShen, XiaoZhou, TuoJi, JiaruiFang, JieZhou.
91.	TAPAS Paper	by Jonathan Herzig, Paweł Krzysztof Nowak, Thomas Müller, Francesco Piccinno and Julian Martin Eisenschlos.
92.	UPerNet Paper	by Tete Xiao, Yingcheng Liu, Bolei Zhou, Yuning Jiang, Jian Sun.
93.	Vision Transformer (ViT) Paper	by Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, Neil Houlsby.
94.	Wav2Vec2 Paper	by Alexei Baevski, Henry Zhou, Abdelrahman Mohamed, Michael Auli.
95.	PLBart Paper	by Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, Kai-Wei Chang.
96.	DiT Paper	by Junlong Li, Yiheng Xu, Tengchao Lv, Lei Cui, Cha Zhang, Furu Wei.
97.	DPR Paper	by Vladimir Karpukhin, Barlas Oğuz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih.
98.	GLPN Paper	by Doyeon Kim, Woonghyun Ga, Pyungwhan Ahn, Donggyu Joo, Sehwan Chun, Junmo Kim.
99.	LeViT Paper	by Ben Graham, Alaaeldin El-Nouby, Hugo Touvron, Pierre Stock, Armand Joulin, Hervé Jégou, Matthijs Douze.
100.	NAT Paper	by Ali Hassani, Steven Walton, Jiachen Li, Shen Li, and Humphrey Shi.
101.	TAPEX Paper	by Qian Liu, Bei Chen, Jiaqi Guo, Morteza Ziyadi, Zeqi Lin, Weizhu Chen, Jian-Guang Lou.
102.	VideoMAE Paper	by Zhan Tong, Yibing Song, Jue Wang, Limin Wang.
103.	Wav2Vec2-Conformer Paper	by Changhan Wang, Yun Tang, Xutai Ma, Anne Wu, Sravya Popuri, Dmytro Okhonko, Juan Pino.
104.	CLIP Paper	by Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, Ilya Sutskever.
105.	XLS-R Paper	by Arun Babu, Changhan Wang, Andros Tjandra, Kushal Lakhotia, Qiantong Xu, Naman Goyal, Kritika Singh, Patrick von Platen, Yatharth Saraf, Juan Pino, Alexei Baevski, Alexis Conneau, Michael Auli.
106.	Audio Spectrogram Transformer Paper	by Yuan Gong, Yu-An Chung, James Glass.
107.	M2M100 Paper	by Angela Fan, Shruti Bhosale, Holger Schwenk, Zhiyi Ma, Ahmed El-Kishky, Siddharth Goyal, Mandeep Baines, Onur Celebi, Guillaume Wenzek, Vishrav Chaudhary, Naman Goyal, Tom Birch, Vitaliy Liptchinsky, Sergey Edunov, Edouard Grave, Michael Auli, Armand Joulin.
108.	MEGA Paper	by Xuezhe Ma, Chunting Zhou, Xiang Kong, Junxian He, Liangke Gui, Graham Neubig, Jonathan May, and Luke Zettlemoyer.
109.	BEiT Paper	by Hangbo Bao, Li Dong, Furu Wei.
110.	BigBird-Pegasus Paper	by Manzil Zaheer, Guru Guruganesh, Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Ontanon, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, Amr Ahmed.
111.	BigBird-RoBERTa Paper	by Manzil Zaheer, Guru Guruganesh, Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Ontanon, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, Amr Ahmed.
112.	CLIPSeg Paper	by Timo Lüddecke and Alexander Ecker.
113.	DPT Paper	by René Ranftl, Alexey Bochkovskiy, Vladlen Koltun.
114.	Perceiver IO Paper	by Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, João Carreira.
115.	Reformer Paper	by Nikita Kitaev, Łukasz Kaiser, Anselm Levskaya.
116.	RoFormer Paper	by Jianlin Su and Yu Lu and Shengfeng Pan and Bo Wen and Yunfeng Liu.
117.	Swin Transformer Paper	by Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, Baining Guo.
118.	TrOCR Paper	by Minghao Li, Tengchao Lv, Lei Cui, Yijuan Lu, Dinei Florencio, Cha Zhang, Zhoujun Li, Furu Wei.
119.	Wav2Vec2Phoneme Paper	by Qiantong Xu, Alexei Baevski, Michael Auli.
120.	X-CLIP Paper	by Bolin Ni, Houwen Peng, Minghao Chen, Songyang Zhang, Gaofeng Meng, Jianlong Fu, Shiming Xiang, Haibin Ling.
121.	XLSR-Wav2Vec2 Paper	by Alexis Conneau, Alexei Baevski, Ronan Collobert, Abdelrahman Mohamed, Michael Auli.
122.	Blenderbot Paper	by Stephen Roller, Emily Dinan, Naman Goyal, Da Ju, Mary Williamson, Yinhan Liu, Jing Xu, Myle Ott, Kurt Shuster, Eric M. Smith, Y-Lan Boureau, Jason Weston.
123.	BlenderbotSmall Paper	by Stephen Roller, Emily Dinan, Naman Goyal, Da Ju, Mary Williamson, Yinhan Liu, Jing Xu, Myle Ott, Kurt Shuster, Eric M. Smith, Y-Lan Boureau, Jason Weston.
124.	BLIP Paper	by Junnan Li, Dongxu Li, Caiming Xiong, Steven Hoi.
125.	ByT5 Paper	by Linting Xue, Aditya Barua, Noah Constant, Rami Al-Rfou, Sharan Narang, Mihir Kale, Adam Roberts, Colin Raffel.
126.	CvT Paper	by Haiping Wu, Bin Xiao, Noel Codella, Mengchen Liu, Xiyang Dai, Lu Yuan, Lei Zhang.
127.	DeBERTa-v2 Paper	by Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen.
128.	DeiT Paper	by Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, Hervé Jégou.
129.	GroupViT Paper	by Jiarui Xu, Shalini De Mello, Sifei Liu, Wonmin Byeon, Thomas Breuel, Jan Kautz, Xiaolong Wang.
130.	LayoutLMv2 Paper	by Yang Xu, Yiheng Xu, Tengchao Lv, Lei Cui, Furu Wei, Guoxin Wang, Yijuan Lu, Dinei Florencio, Cha Zhang, Wanxiang Che, Min Zhang, Lidong Zhou.
131.	MaskFormer Paper	by Bowen Cheng, Alexander G. Schwing, Alexander Kirillov.
132.	SegFormer Paper	by Enze Xie, Wenhai Wang, Zhiding Yu, Anima Anandkumar, Jose M. Alvarez, Ping Luo.
133.	Time Series Transformer Paper
134.	TimeSformer Paper	by Gedas Bertasius, Heng Wang, Lorenzo Torresani.
135.	Trajectory Transformer Paper	by Michael Janner, Qiyang Li, Sergey Levine
136.	UniSpeech Paper	by Chengyi Wang, Yu Wu, Yao Qian, Kenichi Kumatani, Shujie Liu, Furu Wei, Michael Zeng, Xuedong Huang.
137.	UniSpeechSat Paper	by Sanyuan Chen, Yu Wu, Chengyi Wang, Zhengyang Chen, Zhuo Chen, Shujie Liu, Jian Wu, Yao Qian, Furu Wei, Jinyu Li, Xiangzhan Yu.
138.	ALIGN Paper	by Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc V. Le, Yunhsuan Sung, Zhen Li, Tom Duerig.
139.	BORT Paper	by Adrian de Wynter and Daniel J. Perry.
140.	DePlot Paper	by Fangyu Liu, Julian Martin Eisenschlos, Francesco Piccinno, Syrine Krichene, Chenxi Pang, Kenton Lee, Mandar Joshi, Wenhu Chen, Nigel Collier, Yasemin Altun.
141.	DETA Paper	by Jeffrey Ouyang-Zhang, Jang Hyun Cho, Xingyi Zhou, Philipp Krähenbühl.
142.	DiNAT Paper	by Ali Hassani and Humphrey Shi.
143.	Jukebox Paper	by Prafulla Dhariwal, Heewoo Jun, Christine Payne, Jong Wook Kim, Alec Radford, Ilya Sutskever.
144.	mBART-50 Paper	by Yuqing Tang, Chau Tran, Xian Li, Peng-Jen Chen, Naman Goyal, Vishrav Chaudhary, Jiatao Gu, Angela Fan.
145.	Nyströmformer Paper	by Yunyang Xiong, Zhanpeng Zeng, Rudrasis Chakraborty, Mingxing Tan, Glenn Fung, Yin Li, Vikas Singh.
146.	ViT Hybrid Paper	by Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, Neil Houlsby.
147.	X-MOD Paper	by Jonas Pfeiffer, Naman Goyal, Xi Lin, Xian Li, James Cross, Sebastian Riedel, Mikel Artetxe.
148.	BARTpho Paper	by Nguyen Luong Tran, Duong Minh Le and Dat Quoc Nguyen.
149.	BridgeTower Paper	by Xiao Xu, Chenfei Wu, Shachar Rosenman, Vasudev Lal, Wanxiang Che, Nan Duan.
150.	CodeGen Paper	by Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, Caiming Xiong.
151.	GPT-J Paper	by Ben Wang and Aran Komatsuzaki.
152.	LLaMA Paper	by Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Edouard Grave, Guillaume Lample.
153.	MarkupLM Paper	by Junlong Li, Yiheng Xu, Lei Cui, Furu Wei.
154.	PoolFormer Paper	by Yu, Weihao and Luo, Mi and Zhou, Pan and Si, Chenyang and Zhou, Yichen and Wang, Xinchao and Feng, Jiashi and Yan, Shuicheng.
155.	QDQBert Paper	by Hao Wu, Patrick Judd, Xiaojie Zhang, Mikhail Isaev and Paulius Micikevicius.
156.	ViLT Paper	by Wonjae Kim, Bokyung Son, Ildoo Kim.
157.	BARThez Paper	by Moussa Kamal Eddine, Antoine J.-P. Tixier, Michalis Vazirgiannis.
158.	Donut Paper	by Geewook Kim, Teakgyu Hong, Moonbin Yim, Jeongyeon Nam, Jinyoung Park, Jinyeong Yim, Wonseok Hwang, Sangdoo Yun, Dongyoon Han, Seunghyun Park.
159.	ImageGPT Paper	by Mark Chen, Alec Radford, Rewon Child, Jeffrey Wu, Heewoo Jun, David Luan, Ilya Sutskever.
160.	OPT Paper	by Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen et al.
161.	Splinter Paper	by Ori Ram, Yuval Kirstain, Jonathan Berant, Amir Globerson, Omer Levy.
162.	XGLM Paper	by Xi Victoria Lin, Todor Mihaylov, Mikel Artetxe, Tianlu Wang, Shuohui Chen, Daniel Simig, Myle Ott, Naman Goyal, Shruti Bhosale, Jingfei Du, Ramakanth Pasunuru, Sam Shleifer, Punit Singh Koura, Vishrav Chaudhary, Brian O’Horo, Jeff Wang, Luke Zettlemoyer, Zornitsa Kozareva, Mona Diab, Veselin Stoyanov, Xian Li.
163.	YOSO Paper
164.	EfficientFormer Paper	by Yanyu Li, Geng Yuan, Yang Wen, Ju Hu, Georgios Evangelidis, Sergey Tulyakov, Yanzhi Wang, Jian Ren.
165.	ESM Paper	by Alexander Rives, Joshua Meier, Tom Sercu, Siddharth Goyal, Zeming Lin, Jason Liu, Demi Guo, Myle Ott, C. Lawrence Zitnick, Jerry Ma, and Rob Fergus.
166.	Mask2Former Paper	by Bowen Cheng, Ishan Misra, Alexander G. Schwing, Alexander Kirillov, Rohit Girdhar.
167.	MGP-STR Paper	by Peng Wang, Cheng Da, and Cong Yao.
168.	NLLB Paper	by the NLLB team.
169.	T5v1.1 Paper	by Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu.
170.	TVLT Paper	by Zineng Tang, Jaemin Cho, Yixin Nie, Mohit Bansal.
171.	WavLM Paper	by Sanyuan Chen, Chengyi Wang, Zhengyang Chen, Yu Wu, Shujie Liu, Zhuo Chen, Jinyu Li, Naoyuki Kanda, Takuya Yoshioka, Xiong Xiao, Jian Wu, Long Zhou, Shuo Ren, Yanmin Qian, Yao Qian, Jian Wu, Michael Zeng, Furu Wei.
172.	XLM-RoBERTa-XL Paper	by Naman Goyal, Jingfei Du, Myle Ott, Giri Anantharaman, Alexis Conneau.
173.	Chinese-CLIP Paper	by An Yang, Junshu Pan, Junyang Lin, Rui Men, Yichang Zhang, Jingren Zhou, Chang Zhou.
174.	CLAP Paper
175.	Decision Transformer Paper	by Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch.
176.	BLIP-2 Paper	by Junnan Li, Dongxu Li, Silvio Savarese, Steven Hoi.
177.	CANINE Paper	by Jonathan H. Clark, Dan Garrette, Iulia Turc, John Wieting.
178.	Graphormer Paper	by Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu.
179.	I-BERT Paper	by Sehoon Kim, Amir Gholami, Zhewei Yao, Michael W. Mahoney, Kurt Keutzer.
180.	MatCha Paper	by Fangyu Liu, Francesco Piccinno, Syrine Krichene, Chenxi Pang, Kenton Lee, Mandar Joshi, Yasemin Altun, Nigel Collier, Julian Martin Eisenschlos.
181.	mLUKE Paper	by Ryokan Ri, Ikuya Yamada, and Yoshimasa Tsuruoka.
182.	MobileViT Paper	by Sachin Mehta and Mohammad Rastegari.
183.	OWL-ViT Paper	by Matthias Minderer, Alexey Gritsenko, Austin Stone, Maxim Neumann, Dirk Weissenborn, Alexey Dosovitskiy, Aravindh Mahendran, Anurag Arnab, Mostafa Dehghani, Zhuoran Shen, Xiao Wang, Xiaohua Zhai, Thomas Kipf, and Neil Houlsby.
184.	SpeechT5 Paper	by Junyi Ao, Rui Wang, Long Zhou, Chengyi Wang, Shuo Ren, Yu Wu, Shujie Liu, Tom Ko, Qing Li, Yu Zhang, Zhihua Wei, Yao Qian, Jinyu Li, Furu Wei.
185.	Swin Transformer V2 Paper	by Ze Liu, Han Hu, Yutong Lin, Zhuliang Yao, Zhenda Xie, Yixuan Wei, Jia Ning, Yue Cao, Zheng Zhang, Li Dong, Furu Wei, Baining Guo.
186.	ViTMAE Paper	by Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, Ross Girshick.
187.	BLOOM Paper
188.	ConvNeXTV2 Paper	by Sanghyun Woo, Shoubhik Debnath, Ronghang Hu, Xinlei Chen, Zhuang Liu, In So Kweon, Saining Xie.
189.	CPM-Ant Paper
190.	GPT-Sw3 Paper	by Ariel Ekgren, Amaru Cuba Gyllensten, Evangelia Gogoulou, Alice Heiman, Severine Verlinden, Joey Öhman, Fredrik Carlsson, Magnus Sahlgren.
191.	LongT5 Paper	by Mandy Guo, Joshua Ainslie, David Uthus, Santiago Ontanon, Jianmo Ni, Yun-Hsuan Sung, Yinfei Yang.
192.	OneFormer Paper	by Jitesh Jain, Jiachen Li, MangTik Chiu, Ali Hassani, Nikita Orlov, Humphrey Shi.
193.	Table Transformer Paper	by Brandon Smock, Rohith Pesala, Robin Abraham.
194.	VAN Paper	by Meng-Hao Guo, Cheng-Ze Lu, Zheng-Ning Liu, Ming-Ming Cheng, Shi-Min Hu.
195.	AltCLIP Paper	by Chen, Zhongzhi and Liu, Guang and Zhang, Bo-Wen and Ye, Fulong and Yang, Qinghong and Wu, Ledell.
196.	MVP Paper	by Tianyi Tang, Junyi Li, Wayne Xin Zhao and Ji-Rong Wen.
197.	NLLB-MOE Paper	by the NLLB team.
198.	PEGASUS-X Paper	by Jason Phang, Yao Zhao, and Peter J. Liu.
199.	Swin2SR Paper	by Marcos V. Conde, Ui-Jin Choi, Maxime Burchi, Radu Timofte.
200.	UL2 Paper	by Yi Tay, Mostafa Dehghani, Vinh Q. Tran, Xavier Garcia, Dara Bahri, Tal Schuster, Huaixiu Steven Zheng, Neil Houlsby, Donald Metzler
201.	ViTMSN Paper	by Mahmoud Assran, Mathilde Caron, Ishan Misra, Piotr Bojanowski, Florian Bordes, Pascal Vincent, Armand Joulin, Michael Rabbat, Nicolas Ballas.
202.	YOLOS Paper	by Yuxin Fang, Bencheng Liao, Xinggang Wang, Jiemin Fang, Jiyang Qi, Rui Wu, Jianwei Niu, Wenyu Liu.
203.	FLAN-T5 Paper	by Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Zhao, Yanping Huang, Andrew Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, and Jason Wei
204.	GPT NeoX Japanese Paper
205.	LayoutLMv3 Paper	by Yupan Huang, Tengchao Lv, Lei Cui, Yutong Lu, Furu Wei.
206.	FLAN-UL2 Paper	by Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Zhao, Yanping Huang, Andrew Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, and Jason Wei
207.	FLAVA Paper	by Amanpreet Singh, Ronghang Hu, Vedanuj Goswami, Guillaume Couairon, Wojciech Galuba, Marcus Rohrbach, and Douwe Kiela.

Conclusion

I hope this article gave you an idea about Transformer architecture, their variants, their types, their birth chronology and the creators. As we have seen, the Transformer architecture has been a game-changer in natural language processing and computer vision tasks. It has been instrumental in enabling breakthroughs in machine translation, language understanding, and image classification, among other fields.

There are many types of Transformers, such as autoregressive models like GPT, autoencoding models like BERT and its variants, and hybrid models that combine the strengths of both. Additionally, there are many variants of the Transformer architecture, such as XLNet, RoBERTa, and T5, each with their unique contributions and improvements.

The Transformer’s birth chronology spans just a few years, from the original paper in 2017 to the latest models that are being developed today. Its creators include some of the most prominent names in the field of AI, such as Google, Facebook, and OpenAI.

As AI technology continues to evolve, we can expect more exciting developments in the field of Transformers, with even more powerful and sophisticated models that can tackle even more complex tasks. The Transformer architecture has shown us that there is still much to explore in the world of deep learning, and we can’t wait to see what the future holds.