Papers: Difference between revisions

|[[ImageNet Classification with Deep Convolutional Neural Networks (AlexNet)]] || 2012 || [https://proceedings.neurips.cc/paper/2012/file/c399862d3b9d6b76c8436e924a68c45b-Paper.pdf 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]] ||  

|[[Asynchronous Methods for Deep Reinforcement Learning (A3C)]] || 2016/02/04 || [[arxiv:1602.01783]] ||  

|[[Attention Is All You Need (Transformer)]] || 2017/06/12 || [[arxiv:1706.03762]] || influential paper that introduced [[Transformer]]

|[[Proximal Policy Optimization Algorithms (PPO)]] || 2017/07/20 || [[arxiv:1707.06347]] ||  

|[[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]]<br>[https://openai.com/blog/clip/ 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