# AI-Surveys

**Repository Path**: wtadota/AI-Surveys

## Basic Information

- **Project Name**: AI-Surveys
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-10-10
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# AI-Surveys

本repo主要整理AI相关领域的一些综述，起因是看到了 [ml-survey](https://github.com/eugeneyan/ml-surveys) 这个非常棒的项目。

目前添加了『自然语言处理』模块的部分觉得不错的综述。

欢迎有兴趣的小伙伴们一起整理。



## 自然语言处理
- 深度学习： [Recent Trends in Deep Learning Based Natural Language Processing](https://arxiv.org/pdf/1708.02709.pdf "Recent Trends in Deep Learning Based Natural Language Processing")
- 文本分类： [Deep Learning Based Text Classification: A Comprehensive Review](https://arxiv.org/pdf/2004.03705 "Deep Learning Based Text Classification: A Comprehensive Review")
- 文本生成： [Survey of the SOTA in Natural Language Generation: Core tasks, applications and evaluation](https://www.jair.org/index.php/jair/article/view/11173/26378 "Survey of the SOTA in Natural Language Generation: Core tasks, applications and evaluation")
- 文本生成： [Neural Language Generation: Formulation, Methods, and Evaluation](https://arxiv.org/pdf/2007.15780.pdf "Neural Language Generation: Formulation, Methods, and Evaluation")
- 迁移学习： [Exploring Transfer Learning with T5: the Text-To-Text Transfer Transformer](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html "Exploring Transfer Learning with T5: the Text-To-Text Transfer Transformer") ([Paper](https://arxiv.org/abs/1910.10683 "Paper"))
- 迁移学习：[Neural Transfer Learning for Natural Language Processing](https://aran.library.nuigalway.ie/handle/10379/15463)
- 知识图谱：[A Survey on Knowledge Graphs: Representation, Acquisition and Applications](https://arxiv.org/abs/2002.00388 "A Survey on Knowledge Graphs: Representation, Acquisition and Applications")
- 命名实体识别：[A Survey on Deep Learning for Named Entity Recognition](https://arxiv.org/abs/1812.09449 "A Survey on Deep Learning for Named Entity Recognition")
- 关系抽取：[More Data, More Relations, More Context and More Openness: A Review and Outlook for Relation Extraction](https://arxiv.org/abs/2004.03186 "More Data, More Relations, More Context and More Openness: A Review and Outlook for Relation Extraction")
- 情感分析：[Deep Learning for Sentiment Analysis : A Survey](https://arxiv.org/abs/1801.07883)
- ABSA情感分析：[Deep Learning for Aspect-Level Sentiment Classification: Survey, Vision, and Challenges](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8726353)
- 文本匹配：[Neural Network Models for Paraphrase Identification, Semantic Textual Similarity, Natural Language Inference, and Question Answering](https://www.aclweb.org/anthology/C18-1328/)
- 阅读理解：[Neural Reading Comprehension And Beyond](https://stacks.stanford.edu/file/druid:gd576xb1833/thesis-augmented.pdf)
- 阅读理解：[Neural Machine Reading Comprehension: Methods and Trends](https://arxiv.org/abs/1907.01118)
- 机器翻译：[Neural Machine Translation: A Review](https://arxiv.org/abs/1912.02047)
- 机器翻译：[A Survey of Domain Adaptation for Neural Machine Translation](https://www.aclweb.org/anthology/C18-1111.pdf)
- 预训练模型：[Pre-trained Models for Natural Language Processing: A Survey](https://arxiv.org/abs/2003.08271 "Pre-trained Models for Natural Language Processing: A Survey")
- 注意力机制：[An Attentive Survey of Attention Models](https://arxiv.org/pdf/1904.02874.pdf)
- 注意力机制：[An Introductory Survey on Attention Mechanisms in NLP Problems](https://arxiv.org/abs/1811.05544)
- 注意力机制：[Attention in Natural Language Processing](https://arxiv.org/abs/1902.02181)
- BERT：[A Primer in BERTology: What we know about how BERT works](https://arxiv.org/pdf/2002.12327.pdf)
- [Beyond Accuracy: Behavioral Testing of NLP Models with CheckList](https://arxiv.org/pdf/2005.04118.pdf "Beyond Accuracy: Behavioral Testing of NLP Models with CheckList")
- [Evaluation of Text Generation: A Survey](https://arxiv.org/pdf/2006.14799.pdf "Evaluation of Text Generation: A Survey")

## 推荐系统
- [Recommender systems survey](http://irntez.ir/wp-content/uploads/2016/12/sciencedirec.pdf "Recommender systems survey")
- [Deep Learning based Recommender System: A Survey and New Perspectives](https://arxiv.org/pdf/1707.07435.pdf "Deep Learning based Recommender System: A Survey and New Perspectives")
- [Are We Really Making Progress? A Worrying Analysis of Neural Recommendation Approaches](https://arxiv.org/pdf/1907.06902.pdf "Are We Really Making Progress? A Worrying Analysis of Neural Recommendation Approaches")
- [A Survey of Serendipity in Recommender Systems](https://www.researchgate.net/publication/306075233_A_Survey_of_Serendipity_in_Recommender_Systems "A Survey of Serendipity in Recommender Systems")
- [Diversity in Recommender Systems – A survey](https://papers-gamma.link/static/memory/pdfs/153-Kunaver_Diversity_in_Recommender_Systems_2017.pdf "Diversity in Recommender Systems – A survey")
- [A Survey of Explanations in Recommender Systems](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.418.9237&rep=rep1&type=pdf "A Survey of Explanations in Recommender Systems")

## 深度学习
- [A State-of-the-Art Survey on Deep Learning Theory and Architectures](https://www.mdpi.com/2079-9292/8/3/292/htm "A State-of-the-Art Survey on Deep Learning Theory and Architectures")
- 知识蒸馏：[Knowledge Distillation: A Survey](https://arxiv.org/pdf/2006.05525.pdf "Knowledge Distillation: A Survey")
- 模型压缩： [Compression of Deep Learning Models for Text: A Survey](https://arxiv.org/pdf/2008.05221.pdf "Compression of Deep Learning Models for Text: A Survey")
- 迁移学习： [A Survey on Deep Transfer Learning](https://arxiv.org/pdf/1808.01974.pdf "A Survey on Deep Transfer Learning")
- 神经架构搜索： [A Comprehensive Survey of Neural Architecture Search-- Challenges and Solutions](https://arxiv.org/abs/2006.02903 "A Comprehensive Survey of Neural Architecture Search-- Challenges and Solutions")
- 神经架构搜索： [Neural Architecture Search: A Survey](https://arxiv.org/abs/1808.05377 "Neural Architecture Search: A Survey")

## 计算机视觉
- 目标检测： [Object Detection in 20 Years](https://arxiv.org/pdf/1905.05055.pdf "Object Detection in 20 Years")
- 对抗性攻击：[Threat of Adversarial Attacks on Deep Learning in Computer Vision](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8294186 "Threat of Adversarial Attacks on Deep Learning in Computer Vision")
- 自动驾驶：[Computer Vision for Autonomous Vehicles: Problems, Datasets and State of the Art](https://arxiv.org/pdf/1704.05519.pdf "Computer Vision for Autonomous Vehicles: Problems, Datasets and State of the Art")

## 强化学习
- [A Brief Survey of Deep Reinforcement Learning](https://arxiv.org/pdf/1708.05866.pdf "A Brief Survey of Deep Reinforcement Learning")
-  [Transfer Learning for Reinforcement Learning Domains](http://www.jmlr.org/papers/volume10/taylor09a/taylor09a.pdf "Transfer Learning for Reinforcement Learning Domains")
-  [Review of Deep Reinforcement Learning Methods and Applications in Economics](https://arxiv.org/pdf/2004.01509.pdf "Review of Deep Reinforcement Learning Methods and Applications in Economics")

## Embeddings
- 图： [A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications](https://arxiv.org/pdf/1709.07604 "A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications")
- 文本： [From Word to Sense Embeddings:A Survey on Vector Representations of Meaning](https://www.jair.org/index.php/jair/article/view/11259/26454 "From Word to Sense Embeddings:A Survey on Vector Representations of Meaning")
- 文本： [Diachronic Word Embeddings and Semantic Shifts](https://arxiv.org/pdf/1806.03537.pdf "Diachronic Word Embeddings and Semantic Shifts")
- 文本： [Word Embeddings: A Survey](https://arxiv.org/abs/1901.09069 "Word Embeddings: A Survey")
- [A Survey on Contextual Embeddings](https://arxiv.org/abs/2003.07278 "A Survey on Contextual Embeddings")

## Meta-learning & Few-shot Learning
- [A Survey on Knowledge Graphs: Representation, Acquisition and Applications](https://arxiv.org/abs/2002.00388 "A Survey on Knowledge Graphs: Representation, Acquisition and Applications")
- [Meta-learning for Few-shot Natural Language Processing: A Survey](https://arxiv.org/abs/2007.09604 "Meta-learning for Few-shot Natural Language Processing: A Survey")
- [Learning from Few Samples: A Survey](https://arxiv.org/abs/2007.15484 "Learning from Few Samples: A Survey")
- [Meta-Learning in Neural Networks: A Survey](https://arxiv.org/abs/2004.05439 "Meta-Learning in Neural Networks: A Survey")
- [A Comprehensive Overview and Survey of Recent Advances in Meta-Learning](https://arxiv.org/abs/2004.11149 "A Comprehensive Overview and Survey of Recent Advances in Meta-Learning")
- [Baby steps towards few-shot learning with multiple semantics](https://arxiv.org/abs/1906.01905 "Baby steps towards few-shot learning with multiple semantics")
- [Meta-Learning: A Survey](https://arxiv.org/abs/1810.03548 "Meta-Learning: A Survey")
- [A Perspective View And Survey Of Meta-learning](https://www.researchgate.net/publication/2375370_A_Perspective_View_And_Survey_Of_Meta-Learning "A Perspective View And Survey Of Meta-learning")

## 其他
- [A Survey on Transfer Learning](http://202.120.39.19:40222/wp-content/uploads/2018/03/A-Survey-on-Transfer-Learning.pdf "A Survey on Transfer Learning")