本repo主要整理AI相关领域的一些综述，起因是看到了 ml-survey 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。
Table of Contents
- 自然语言处理 (NLP)
- 推荐系统 (Recommender System)
- 深度学习 (Deep Learning)
- 计算机视觉 (Computer Vision)
- 图网络 (Graph Network)
- 强化学习 (Reinforcement Learning)
- 向量化 (Embeddings)
- 多任务学习 (Multi-Task Learning)
- Meta-learning & Few-shot Learning
- 搜索推荐
- Others
- Deep Learning Based Text Classification: A Comprehensive Review
- A Survey on Data Augmentation for Text Classification
- Deep Learning for Sentiment Analysis : A Survey
- Deep Learning for Aspect-Level Sentiment Classification: Survey, Vision, and Challenges
- More Data, More Relations, More Context and More Openness: A Review and Outlook for Relation Extraction
- A Survey of Deep Learning Methods for Relation Extraction
- Neural Network Models for Paraphrase Identification, Semantic Textual Similarity, Natural Language Inference, and Question Answering
- 深度文本匹配综述
- Pretrained Transformers for Text Ranking: BERT and Beyond
- Neural Reading Comprehension And Beyond
- Neural Machine Reading Comprehension: Methods and Trends
- Machine Reading Comprehension: The Role of Contextualized Language Models and Beyond
- Machine Reading Comprehension: a Literature Review
- Neural Machine Translation: A Review
- A Survey of Domain Adaptation for Neural Machine Translation
- Neural Machine Translation: Challenges, Progress and Future
- A Survey of Methods to Leverage Monolingual Data in Low-resource Neural Machine Translation
- A Comprehensive Survey of Multilingual Neural Machine Translation
- A Survey of Deep Learning Techniques for Neural Machine Translation
- A Survey on Document-level Machine Translation: Methods and Evaluation
- A Survey of Knowledge-Enhanced Text Generation
- Neural Language Generation: Formulation, Methods, and Evaluation
- Survey of the SOTA in Natural Language Generation: Core tasks, applications and evaluation
- Evaluation of Text Generation: A Survey
- Recent Advances in Neural Question Generation
- Neural Text Generation: Past, Present and Beyond
- Pretrained Language Models for Text Generation: A Survey
- Recent Advances and Challenges in Task-oriented Dialog System
- Neural Approaches to Conversational AI
- Challenges in Building Intelligent Open-domain Dialog Systems
- How Far are We from Effective Context Modeling? An Exploratory Study on Semantic Parsing in Context
- A Survey on Dialogue Summarization: Recent Advances and New Frontiers
- A Survey on Knowledge Graphs: Representation, Acquisition and Applications
- Core techniques of question answering systems over knowledge bases: a survey
- Introduction to Neural Network based Approaches for Question Answering over Knowledge Graphs
- Recent Trends in Deep Learning Based Natural Language Processing
- A Survey of the Usages of Deep Learning in Natural Language Processing
- Exploring Transfer Learning with T5: the Text-To-Text Transfer Transformer (Paper)
- Neural Transfer Learning for Natural Language Processing
- Pre-trained Models for Natural Language Processing: A Survey
- A Primer in BERTology: What we know about how BERT works
- An Attentive Survey of Attention Models
- An Introductory Survey on Attention Mechanisms in NLP Problems
- Attention in Natural Language Processing
- A Survey of Data Augmentation Approaches for NLP
- Beyond Accuracy: Behavioral Testing of NLP Models with CheckList
- Analysis Methods in Neural Language Processing: A Survey
- A Primer on Neural Network Models for Natural Language Processing
- A Survey on Neural Recommendation: From Collaborative Filtering to Content and Context Enriched Recommendation
- Recommender systems survey
- Deep Learning based Recommender System: A Survey and New Perspectives
- Are We Really Making Progress? A Worrying Analysis of Neural Recommendation Approaches
- A Survey of Serendipity in Recommender Systems
- Diversity in Recommender Systems – A survey
- A Survey of Explanations in Recommender Systems
- A Survey on Knowledge Graph-Based Recommender Systems
- Adversarial Machine Learning in Recommender Systems: State of the art and Challenges
- Graph Learning Approaches to Recommender Systems: A Review
- A State-of-the-Art Survey on Deep Learning Theory and Architectures
- 知识蒸馏：Knowledge Distillation: A Survey
- 模型压缩： Compression of Deep Learning Models for Text: A Survey
- 迁移学习： A Survey on Deep Transfer Learning
- 神经架构搜索： A Comprehensive Survey of Neural Architecture Search-- Challenges and Solutions
- 神经架构搜索： Neural Architecture Search: A Survey
- 目标检测： Object Detection in 20 Years
- 对抗性攻击：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
- Foundations and modelling of dynamic networks using Dynamic Graph Neural Networks: A survey
- Introduction to Graph Neural Networks
- A Practical Guide to Graph Neural Networks
- Graph Neural Networks: A Review of Methods and Applications
- A Comprehensive Survey on Graph Neural Networks
- Deep Learning on Graphs: A Survey
- Adversarial Attack and Defense on Graph Data: A Survey
- The Graph Neural Network Model
- Benchmarking Graph Neural Networks
- A Brief Survey of Deep Reinforcement Learning
- Transfer Learning for Reinforcement Learning Domains
- Review of Deep Reinforcement Learning Methods and Applications in Economics
- 图： A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applications
- 文本： From Word to Sense Embeddings:A Survey on Vector Representations of Meaning
- 文本： Diachronic Word Embeddings and Semantic Shifts
- 文本： Word Embeddings: A Survey
- A Survey on Contextual Embeddings
- Multi-Task Learning for Dense Prediction Tasks: A Survey
- An overview of multi-task learning
- A Survey on Multi-Task Learning
- Multi-Task Learning with Deep Neural Networks: A Survey
- A Comparison of Loss Weighting Strategies for Multi task Learning in Deep Neural Networks
- Multi-task learning for natural language processing in the 2020s: Where are we going?
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- A Survey on Knowledge Graphs: Representation, Acquisition and Applications
- Meta-learning for Few-shot Natural Language Processing: A Survey
- Learning from Few Samples: A Survey
- Meta-Learning in Neural Networks: A Survey
- A Comprehensive Overview and Survey of Recent Advances in Meta-Learning
- Baby steps towards few-shot learning with multiple semantics
- Meta-Learning: A Survey
- A Perspective View And Survey Of Meta-learning
- Deep Learning based Recommender System: A Survey and New Perspectives
- A Survey on Knowledge Graph-Based Recommender Systems
- Graph Learning Approaches to Recommender Systems: A Review
- Adversarial Machine Learning in Recommender Systems: State of the art and Challenges
- Graph Neural Networks in Recommender Systems: A Survey
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent