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https://github.com/karims/awesome-ml-survey-papers

List of curated survey papers in machine/deep learning
https://github.com/karims/awesome-ml-survey-papers

List: awesome-ml-survey-papers

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List of curated survey papers in machine/deep learning

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# awesome-ml-survey-papers

List of curated survey papers in machine/deep learning



# Table of contents

1. [Transformers](#transformers)

2. [NLP](#paragraph1)

    1. [Reading comprehension](#rc)

    2. [Text generation](#tg)

    3. [Question Answering](#qa)

    4. [Conversational](#cc)

    5. [Code generation](#cg)

    6. [Data augmentation](#dataaug)

    7. [Other](#subparagraph3)

3. [Vision](#vision)

    1. [Images](#images)

    2. [Image captioning](#ic)

    3. [Image segmentation](#is)

    4. [Video](#video)

    5. [Other](#otherimg)

4. [Applications](#applications)

    1. [Medical](#medical)

    2. [Material science](#material)



## Transformers 

1. [A Survey of Transformers](https://arxiv.org/abs/2106.04554) T Lin, Y Wang, X Liu, X Qiu - arXiv preprint arXiv:2106.04554, 2021 

2. [Transformers in Vision: A Survey](https://arxiv.org/abs/2101.01169) S Khan, M Naseer, M Hayat, SW Zamir… - arXiv preprint arXiv 2021

3. [A Survey on Vision Transformer](https://arxiv.org/abs/2012.12556) Kai Han, Yunhe Wang, Hanting Chen, Xinghao Chen, Jianyuan Guo..- 	arXiv:2012.12556 arXiv 2021

4. [Practical Survey on Faster and Lighter Transformers](https://arxiv.org/abs/2103.14636) Q Fournier, GM Caron, D Aloise - arXiv preprint arXiv:2103.14636, 2021

5. [Efficient transformers: A survey](https://arxiv.org/abs/2009.06732) Y Tay, M Dehghani, D Bahri, D Metzler - arXiv preprint arXiv:2009.06732, 2020

6. [Survey: Transformer based Video-Language Pre-training](https://arxiv.org/abs/2109.09920) Ludan Ruan, Qin Jin, 2021 - arXiv:2109.09920 



## NLP 

Sub-categorized as below:



### Reading comprehension 

1. [A Survey on Machine Reading Comprehension—Tasks, Evaluation Metrics and Benchmark Datasets](https://www.mdpi.com/873696) C Zeng, S Li, Q Li, J Hu, J Hu - Applied Sciences, 2020 - mdpi.com



### Text generation 

1. [Pretrained Language Models for Text Generation: A Survey](https://arxiv.org/abs/2105.10311) Junyi Li, Tianyi Tang, Wayne Xin Zhao, Ji-Rong Wen 	arXiv:2105.10311, 2021

2. [The survey: Text generation models in deep learning](https://www.sciencedirect.com/science/article/pii/S1319157820303360)

3. [A survey of evaluation metrics used for NLG systems](https://arxiv.org/abs/2008.12009) AB Sai, AK Mohankumar, MM Khapra - arXiv preprint arXiv:2008.12009, 2020

4. [Towards User-Centric Text-to-Text Generation: A Survey](https://link.springer.com/chapter/10.1007/978-3-030-83527-9_1) Diyi Yang, Lucie Flek



### Question Answering 

1. [Retrieving and Reading: A Comprehensive Survey on Open-domain Question Answering](https://arxiv.org/abs/2101.00774) Fengbin Zhu, Wenqiang Lei, Chao Wang, Jianming Zheng, Soujanya Poria, Tat-Seng Chua... 2021

2. [Conversational Question Answering: A Survey](https://arxiv.org/abs/2106.00874) Munazza Zaib, Wei Emma Zhang, Quan Z. Sheng, Adnan Mahmood, Yang Zhang.. 2021

3. [Visual question answering using deep learning: A survey and performance analysis](https://link.springer.com/chapter/10.1007/978-981-16-1092-9_7) Y Srivastava, V Murali, SR Dubey… - … Conference on Computer …, 2020 

4. [Biomedical Question Answering: A Survey of Approaches and Challenges](https://arxiv.org/abs/2102.05281) Qiao Jin, Zheng Yuan, Guangzhi Xiong, Qianlan Yu, Huaiyuan Ying.. 2021

5. [A survey on complex question answering over knowledge base: Recent advances and challenges](https://arxiv.org/abs/2007.13069) B Fu, Y Qiu, C Tang, Y Li, H Yu, J Sun - arXiv preprint arXiv:2007.13069, 2020 

6. [Text-based Question Answering from Information Retrieval and Deep Neural Network Perspectives: A Survey](https://arxiv.org/abs/2002.06612) Zahra Abbasiantaeb, Saeedeh Momtazi..2020



### Conversational 

1. [Conversational Question Answering: A Survey](https://arxiv.org/abs/2106.00874) Munazza Zaib, Wei Emma Zhang, Quan Z. Sheng, Adnan Mahmood, Yang Zhang.. 2021

2. [Advances in Multi-turn Dialogue Comprehension: A Survey](https://arxiv.org/abs/2103.03125) Zhuosheng Zhang, Hai Zhao.. 2021



### Code generation 

This is a sub paragraph, formatted in heading 3 style



### Data augmentation 

1. [An Empirical Survey of Data Augmentation for Limited Data Learning in NLP](https://arxiv.org/abs/2106.07499) Jiaao Chen, Derek Tam, Colin Raffel, Mohit Bansal, Diyi Yang., arXiv:2106.07499

2. [A Survey of Data Augmentation Approaches for NLP](https://arxiv.org/abs/2105.03075)  Steven Y. Feng, Varun Gangal, Jason Wei, Sarath Chandar,... arXiv:2105.03075

3. [A Survey on Machine Learning Techniques for Auto Labeling of Video, Audio, and Text Data](https://arxiv.org/abs/2109.03784) Shikun Zhang, Omid Jafari, Parth Nagarkar



### Other 

1. [A Survey of Race, Racism, and Anti-Racism in NLP](https://arxiv.org/abs/2106.11410) Anjalie Field, Su Lin Blodgett, Zeerak Waseem, Yulia Tsvetkov, 	arXiv:2106.11410, 2021

2. [Language (Technology) is Power: A Critical Survey of “Bias” in NLP](https://aclanthology.org/2020.acl-main.485/) Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna Wallach

3. [Representing Numbers in NLP: a Survey and a Vision](https://arxiv.org/abs/2103.13136) Avijit Thawani, Jay Pujara, Pedro A. Szekely, Filip Ilievski, arXiv:2103.13136, 2021

4. [Visual-and-Language Navigation: A Survey and Taxonomy](https://arxiv.org/abs/2108.11544) Wansen Wu, Tao Chang, Xinmeng Li, 2021



## Vision 

Sub-categorized as below:



### Images 

1. [A survey on Semi-, Self- and Unsupervised Learning for Image Classification](https://arxiv.org/abs/2002.08721) Lars Schmarje, Monty Santarossa, Simon-Martin Schröder, Reinhard Koch.. 2021

2. [A Survey on Deep Visual Place Recognition](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9336674) C Masone, B Caputo , 2021

3.  [Deep Learning for Image Super-resolution: A Survey](https://arxiv.org/abs/1902.06068) Zhihao Wang, Jian Chen, Steven C. H. Hoi.. 2020

4.  [A Survey on Deep Learning-based Architectures for Semantic Segmentation on 2D images](https://arxiv.org/abs/1912.10230) Irem Ulku, Erdem Akagunduz.. 2021

5.  [Low-Light Image and Video Enhancement Using Deep Learning: A Survey](https://arxiv.org/abs/2104.10729) Chongyi Li, Chunle Guo, Linghao Han, Jun Jiang, Ming-Ming Cheng, Jinwei Gu, Chen Change Loy

6.  [A Comprehensive Survey on Image Dehazing Based on Deep Learning](https://arxiv.org/abs/2106.03323) Jie Gui, Xiaofeng Cong, Yuan Cao, Wenqi Ren, Jun Zhang, Jing Zhang, Dacheng Tao.. 2021

7.  [Image Classification with Deep Learning in the Presence of Noisy Labels: A Survey](https://arxiv.org/abs/1912.05170) Görkem Algan, Ilkay Ulusoy.. 2021

8.  [A survey on deep geometry learning: From a representation perspective](https://link.springer.com/content/pdf/10.1007/s41095-020-0174-8.pdf) YP Xiao, YK Lai, FL Zhang, C Li, L Gao - Computational Visual Media, 2020



### Image captioning 

1. [From Show to Tell: A Survey on Image Captioning](https://arxiv.org/abs/2107.06912) Matteo Stefanini, Marcella Cornia, Lorenzo Baraldi,.. 2021

2. [Image Captioning based on Deep Learning Methods: A Survey](https://arxiv.org/abs/1905.08110) Yiyu Wang, Jungang Xu, Yingfei Sun, Ben He.. 2019

3. [A Comprehensive Survey of Deep Learning for Image Captioning](https://arxiv.org/abs/1810.04020) Md. Zakir Hossain, Ferdous Sohel, Mohd Fairuz Shiratuddin, Hamid Laga

4. [A Survey on Biomedical Image Captioning](https://arxiv.org/abs/1905.13302) Vasiliki Kougia, John Pavlopoulos, Ion Androutsopoulos.. 2019



### Image segmentation 

1. [[Image Segmentation Using Deep Learning: A Survey](https://arxiv.org/abs/2001.05566) Shervin Minaee, Yuri Boykov, Fatih Porikli, Antonio Plaza, Nasser Kehtarnavaz, Demetri Terzopoulos... 2020]

2. [A Survey on Deep Learning Methods for Semantic Image Segmentation in Real-Time](https://arxiv.org/abs/2009.12942) Georgios Takos



### Video 

1. [Video Question Answering: a Survey of Models and Datasets](https://link.springer.com/article/10.1007/s11036-020-01730-0) Guanglu Sun, Lili Liang, Tianlin Li, Bo Yu, Meng Wu & Bolun Zhang 



### Other 

1. [A Survey of Hand Crafted and Deep Learning Methods for Image Aesthetic Assessment](https://arxiv.org/abs/2103.11616) Saira Kanwal, Muhammad Uzair and Habib Ullah

2. [Deep Learning for Fine-Grained Image Analysis: A Survey](https://arxiv.org/abs/1907.03069) Xiu-Shen Wei, Jianxin Wu, Quan Cui



## Applications 



### Medical 

1. [Deep learning-enabled medical computer vision](https://www.nature.com/articles/s41746-020-00376-2) A Esteva, K Chou, S Yeung, N Naik, A Madani… 2021

2. [Self-supervised learning methods and applications in medical imaging analysis: A survey](https://arxiv.org/abs/2109.08685) Saeed Shurrab, Rehab Duwiari, 2021

3. [Medical Image Segmentation Using Deep Learning: A Survey](https://arxiv.org/abs/2009.13120) Tao Lei, Risheng Wang, Yong Wan, Bingtao Zhang, Hongying Meng, Asoke K. Nandi.. 2021

4. [Deep Learning for Biomedical Image Reconstruction: A Survey](https://arxiv.org/abs/2002.12351) Hanene Ben Yedder, Ben Cardoen, Ghassan Hamarneh

5. [A State-of-the-art Survey of Object Detection Techniques in Microorganism Image Analysis](https://arxiv.org/abs/2105.03148) Chen Li, Pingli Ma, Md Mamunur Rahaman, Yudong Yao.. 2021

6. [A survey on shape-constraint deep learning for medical image segmentation](https://arxiv.org/abs/2101.07721) Simon Bohlender, Ilkay Oksuz, Anirban Mukhopadhyay.. 2021



### Material science 

1. [MaterialsAtlas.org: A Materials Informatics Web App Platform for Materials Discovery and Survey of State-of-the-Art](https://arxiv.org/abs/2109.04007) Jianjun Hu, Stanislav Stefanov, Yuqi Song, Sadman Sadeed Omee, ... 2021

2. [Deep Learning the Electromagnetic Properties of Metamaterials—A Comprehensive Review](https://en.x-mol.com/paper/article/1398392259059630080) Omar Khatib, Simiao Ren, Jordan Malof, Willie J. Padilla ... 2021