| Name
|
Submission
Date
|
Source
|
Note
|
| ImageNet Classification with Deep Convolutional Neural Networks (AlexNet) |
2012 |
AlexNet Paper |
|
| Playing Atari with Deep Reinforcement Learning (DQN) |
2013/12/19 |
arxiv:1312.5602 |
|
| Very Deep Convolutional Networks for Large-Scale Image Recognition (VGGNet) |
2014/09/04 |
arxiv:409.1556 |
|
| Deep Residual Learning for Image Recognition (ResNet) |
2015/12/10 |
arxiv:409.1556 |
|
| Going Deeper with Convolutions (GoogleNet) |
2015/12/10 |
arxiv:409.1556 |
|
| Attention Is All You Need (Transformer) |
2017/06/12 |
arxiv:1706.03762 |
influential paper that introduced Transformer
|
| Transformer-XL |
2019/01/09 |
arxiv:1901.02860 |
Attentive Language Models Beyond a Fixed-Length Context
|
| Language Models are Few-Shot Learners |
2020/05/28 |
arxiv:2005.14165 |
GPT
|
| An Image is Worth 16x16 Words |
2020/10/22 |
arxiv:2010.11929 |
Transformers for Image Recognition at Scale - Vision Transformer (ViT)
|
| OpenAI CLIP |
2021/02/26 |
arxiv:2103.00020
OpenAI Blog |
Learning Transferable Visual Models From Natural Language Supervision
|
| MobileViT |
2021/10/05 |
arxiv:2110.02178 |
Light-weight, General-purpose, and Mobile-friendly Vision Transformer
|
| Block-Recurrent Transformers |
2022/03/11 |
arxiv:2203.07852 |
|
| Memorizing Transformers |
2022/03/16 |
arxiv:2203.08913 |
|
| STaR |
2022/03/28 |
arxiv:2203.14465 |
Bootstrapping Reasoning With Reasoning
|
