37 minute read


What Are Transformers in AI

Transformer Architecture



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
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.


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.