Papers: Difference between revisions

Revision as of 17:16, 6 February 2023

Certain elements of this article are incomplete. You can help the AI Wiki by expanding it.

Important Papers

Name	Submission Date	Source	Type	Note
ImageNet Classification with Deep Convolutional Neural Networks (AlexNet)	2012	AlexNet Paper		AlexNet
Efficient Estimation of Word Representations in Vector Space (Word2Vec)	2013/01/16	arxiv:1301.3781	NLP	Word2Vec
Playing Atari with Deep Reinforcement Learning (DQN)	2013/12/19	arxiv:1312.5602		DQN
Generative Adversarial Networks (GAN)	2014/06/10	arxiv:1406.2661		GAN
Very Deep Convolutional Networks for Large-Scale Image Recognition (VGGNet)	2014/09/04	arxiv:409.1556		VGGNet
Sequence to Sequence Learning with Neural Networks (Seq2Seq)	2014/09/10	arxiv:1409.3215		Seq2Seq
Adam: A Method for Stochastic Optimization)	2014/12/22	arxiv:1412.6980		Adam
Deep Residual Learning for Image Recognition (ResNet)	2015/12/10	arxiv:409.1556		ResNet
Going Deeper with Convolutions (GoogleNet)	2015/12/10	arxiv:409.1556		GoogleNet
Asynchronous Methods for Deep Reinforcement Learning (A3C)	2016/02/04	arxiv:1602.01783		A3C
WaveNet: A Generative Model for Raw Audio	2016/09/12	arxiv:1609.03499	Audio	WaveNet
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		PPO
Improving Language Understanding by Generative Pre-Training (GPT)	2018	paper source	NLP	GPT
Deep contextualized word representations (ELMo)	2018/02/15	arxiv:1802.05365	NLP	ELMo
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding	2018/04/20	arxiv:1804.07461	NLP	GLUE
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding	2018/10/11	arxiv:1810.04805	NLP	BERT
Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context	2019/01/09	arxiv:1901.02860		Transformer-XL
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model (MuZero)	2019/11/19	arxiv:1911.08265		MuZero
Language Models are Few-Shot Learners (GPT-3)	2020/05/28	arxiv:2005.14165	NLP	GPT-3
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale (ViT)	2020/10/22	arxiv:2010.11929		Vision Transformer (ViT)
Learning Transferable Visual Models From Natural Language Supervision (CLIP)	2021/02/26	arxiv:2103.00020 OpenAI Blog
MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer	2021/10/05	arxiv:2110.02178		MobileViT
Block-Recurrent Transformers	2022/03/11	arxiv:2203.07852
Memorizing Transformers	2022/03/16	arxiv:2203.08913
STaR: Bootstrapping Reasoning With Reasoning	2022/03/28	arxiv:2203.14465		STaR

Other Papers

Name	Submission Date	Source	Organization	Note
Dreamix: Video Diffusion Models are General Video Editors	2023/02/03	arxiv:2302.01329 blog post	Dreamix
FLAME: A small language model for spreadsheet formulas	2023/01/31	arxiv:2301.13779	Microsoft	FLAME
Muse: Text-To-Image Generation via Masked Generative Transformers	2023/01/02	arxiv:2301.00704 blog post	Google	Muse
Constitutional AI: Harmlessness from AI Feedback	2021/12/12	arxiv:2212.08073	Anthropic	Constitutional AI, Claude

@@ Line 80: / Line 80: @@
 |[[Muse: Text-To-Image Generation via Masked Generative Transformers]] || 2023/01/02 ||[[arxiv:2301.00704]]<br>[https://muse-model.github.io/ blog post] || || [[Google]] || [[Muse]]
 |-
-|[[Constitutional AI: Harmlessness from AI Feedback]] || 2021/12/12 || [[arxiv:2212.08073]] ||  || [[Anthropic]] | [[Constitutional AI]], [[Claude]]
+|[[Constitutional AI: Harmlessness from AI Feedback]] || 2021/12/12 || [[arxiv:2212.08073]] ||  || [[Anthropic]] || [[Constitutional AI]], [[Claude]]
 |-
 |}