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A Survey of Surveys (NLP & ML)

In this document, we survey hundreds of survey papers on Natural Language Processing (NLP) and Machine Learning (ML). We categorize these papers into popular topics and do simple counting for some interesting problems. In addition, we show the list of the papers with urls (1063 papers).

🆕 A list of LLM surveys is released! Link

Categorization

We follow the ACL and ICML submission guideline of recent years, covering a broad range of areas in NLP and ML. The categorization is as follows:

To reduce class imbalance, we separate some of the hot sub-topics from the original categorization of ACL and ICML submissions. E.g., Named Entity Recognition is a first-level area in our categorization because it is the focus of several surveys.

Statistics

We show the number of paper in each area in Figures 1-2.

Figure 1: # of papers in each NLP area.

Figure 2: # of papers in each ML area.

Also, we plot paper number as a function of publication year (see Figure 3).

Figure 3: # of papers vs publication year.

In addition, we generate word clouds to show hot topics in these surveys (see Figures 4-5).

Figure 4: The word cloud for NLP.

Figure 5: The word cloud for ML.

The NLP Paper List

  1. A Comprehensive Survey on Community Detection with Deep Learning. arXiv 2021 paper bib

    Xing Su, Shan Xue, Fanzhen Liu, Jia Wu, Jian Yang, Chuan Zhou, Wenbin Hu, Cécile Paris, Surya Nepal, Di Jin, Quan Z. Sheng, Philip S. Yu

  2. A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities. ACM Comput. Surv. 2021 paper bib

    Xinyi Zhou, Reza Zafarani

  3. A Survey of Race, Racism, and Anti-Racism in NLP. ACL 2021 paper bib

    Anjalie Field, Su Lin Blodgett, Zeerak Waseem, Yulia Tsvetkov

  4. A Survey on Computational Propaganda Detection. IJCAI 2020 paper bib

    Giovanni Da San Martino, Stefano Cresci, Alberto Barrón-Cedeño, Seunghak Yu, Roberto Di Pietro, Preslav Nakov

  5. A Survey on Trust Prediction in Online Social Networks. IEEE Access 2020 paper bib

    Seyed Mohssen Ghafari, Amin Beheshti, Aditya Joshi, Cécile Paris, Adnan Mahmood, Shahpar Yakhchi, Mehmet A. Orgun

  6. Computational Sociolinguistics: A Survey. Comput. Linguistics 2016 paper bib

    Dong Nguyen, A. Seza Dogruöz, Carolyn P. Rosé, Franciska de Jong

  7. Confronting Abusive Language Online: A Survey from the Ethical and Human Rights Perspective. J. Artif. Intell. Res. 2021 paper bib

    Svetlana Kiritchenko, Isar Nejadgholi, Kathleen C. Fraser

  8. From Symbols to Embeddings: A Tale of Two Representations in Computational Social Science. J. Soc. Comput. 2021 paper bib

    Huimin Chen, Cheng Yang, Xuanming Zhang, Zhiyuan Liu, Maosong Sun, Jianbin Jin

  9. Language (Technology) is Power: A Critical Survey of "Bias" in NLP. ACL 2020 paper bib

    Su Lin Blodgett, Solon Barocas, Hal Daumé III, Hanna M. Wallach

  10. Societal Biases in Language Generation: Progress and Challenges. ACL 2021 paper bib

    Emily Sheng, Kai-Wei Chang, Prem Natarajan, Nanyun Peng

  11. Tackling Online Abuse: A Survey of Automated Abuse Detection Methods. arXiv 2019 paper bib

    Pushkar Mishra, Helen Yannakoudakis, Ekaterina Shutova

  12. When do Word Embeddings Accurately Reflect Surveys on our Beliefs About People?. ACL 2020 paper bib

    Kenneth Joseph, Jonathan H. Morgan

  1. A Survey of Arabic Dialogues Understanding for Spontaneous Dialogues and Instant Message. arXiv 2015 paper bib

    AbdelRahim A. Elmadany, Sherif M. Abdou, Mervat Gheith

  2. A Survey of Available Corpora For Building Data-Driven Dialogue Systems: The Journal Version. Dialogue Discourse 2018 paper bib

    Iulian Vlad Serban, Ryan Lowe, Peter Henderson, Laurent Charlin, Joelle Pineau

  3. A Survey of Document Grounded Dialogue Systems (DGDS). arXiv 2020 paper bib

    Longxuan Ma, Wei-Nan Zhang, Mingda Li, Ting Liu

  4. A Survey of Intent Classification and Slot-Filling Datasets for Task-Oriented Dialog. arXiv 2022 paper bib

    Stefan Larson, Kevin Leach

  5. A Survey of Natural Language Generation Techniques with a Focus on Dialogue Systems - Past, Present and Future Directions. arXiv 2019 paper bib

    Sashank Santhanam, Samira Shaikh

  6. A survey of neural models for the automatic analysis of conversation: Towards a better integration of the social sciences. arXiv 2022 paper bib

    Chloé Clavel, Matthieu Labeau, Justine Cassell

  7. A Survey on Dialog Management: Recent Advances and Challenges. arXiv 2020 paper bib

    Yinpei Dai, Huihua Yu, Yixuan Jiang, Chengguang Tang, Yongbin Li, Jian Sun

  8. A Survey on Dialogue Systems: Recent Advances and New Frontiers. SIGKDD Explor. 2017 paper bib

    Hongshen Chen, Xiaorui Liu, Dawei Yin, Jiliang Tang

  9. Advances in Multi-turn Dialogue Comprehension: A Survey. arXiv 2021 paper bib

    Zhuosheng Zhang, Hai Zhao

  10. Challenges in Building Intelligent Open-domain Dialog Systems. ACM Trans. Inf. Syst. 2020 paper bib

    Minlie Huang, Xiaoyan Zhu, Jianfeng Gao

  11. Conversational Agents: Theory and Applications. arXiv 2022 paper bib

    Mattias Wahde, Marco Virgolin

  12. Conversational Machine Comprehension: a Literature Review. COLING 2020 paper bib

    Somil Gupta, Bhanu Pratap Singh Rawat, Hong Yu

  13. How to Evaluate Your Dialogue Models: A Review of Approaches. arXiv 2021 paper bib

    Xinmeng Li, Wansen Wu, Long Qin, Quanjun Yin

  14. Neural Approaches to Conversational AI. ACL 2018 paper bib

    Jianfeng Gao, Michel Galley, Lihong Li

  15. Neural Approaches to Conversational AI: Question Answering, Task-oriented Dialogues and Social Chatbots. Now Foundations and Trends 2019 paper bib

    Jianfeng Gao, Michel Galley, Lihong Li

  16. POMDP-Based Statistical Spoken Dialog Systems: A Review. Proc. IEEE 2013 paper bib

    Steve J. Young, Milica Gasic, Blaise Thomson, Jason D. Williams

  17. Recent Advances and Challenges in Task-oriented Dialog System. arXiv 2020 paper bib

    Zheng Zhang, Ryuichi Takanobu, Minlie Huang, Xiaoyan Zhu

  18. Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Survey. arXiv 2021 paper bib

    Jinjie Ni, Tom Young, Vlad Pandelea, Fuzhao Xue, Vinay Adiga, Erik Cambria

  19. Utterance-level Dialogue Understanding: An Empirical Study. arXiv 2020 paper bib

    Deepanway Ghosal, Navonil Majumder, Rada Mihalcea, Soujanya Poria

  1. A Survey of Controllable Text Generation using Transformer-based Pre-trained Language Models. arXiv 2022 paper bib

    Hanqing Zhang, Haolin Song, Shaoyu Li, Ming Zhou, Dawei Song

  2. A Survey of Knowledge-Enhanced Text Generation. ACM Comput. Surv. 2022 paper bib

    Wenhao Yu, Chenguang Zhu, Zaitang Li, Zhiting Hu, Qingyun Wang, Heng Ji, Meng Jiang

  3. A Survey on Multi-hop Question Answering and Generation. arXiv 2022 paper bib

    Vaibhav Mavi, Anubhav Jangra, Adam Jatowt

  4. A Survey on Retrieval-Augmented Text Generation. arXiv 2022 paper bib

    Huayang Li, Yixuan Su, Deng Cai, Yan Wang, Lemao Liu

  5. A Survey on Text Simplification. arXiv 2020 paper bib

    Punardeep Sikka, Vijay Mago

  6. Automatic Detection of Machine Generated Text: A Critical Survey. COLING 2020 paper bib

    Ganesh Jawahar, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan

  7. Automatic Story Generation: Challenges and Attempts. arXiv 2021 paper bib

    Amal Alabdulkarim, Siyan Li, Xiangyu Peng

  8. ChatGPT is not all you need. A State of the Art Review of large Generative AI models. arXiv 2023 paper bib

    Roberto Gozalo-Brizuela, Eduardo C. Garrido-Merchán

  9. Content Selection in Data-to-Text Systems: A Survey. arXiv 2016 paper bib

    Dimitra Gkatzia

  10. Data-Driven Sentence Simplification: Survey and Benchmark. Comput. Linguistics 2020 paper bib

    Fernando Alva-Manchego, Carolina Scarton, Lucia Specia

  11. Deep Learning for Text Style Transfer: A Survey. Comput. Linguistics 2022 paper bib

    Di Jin, Zhijing Jin, Zhiting Hu, Olga Vechtomova, Rada Mihalcea

  12. Evaluation of Text Generation: A Survey. arXiv 2020 paper bib

    Asli Celikyilmaz, Elizabeth Clark, Jianfeng Gao

  13. Human Evaluation of Creative NLG Systems: An Interdisciplinary Survey on Recent Papers. arXiv 2021 paper bib

    Mika Hämäläinen, Khalid Al-Najjar

  14. Keyphrase Generation: A Multi-Aspect Survey. FRUCT 2019 paper bib

    Erion Çano, Ondrej Bojar

  15. Neural Language Generation: Formulation, Methods, and Evaluation. arXiv 2020 paper bib

    Cristina Garbacea, Qiaozhu Mei

  16. Neural Text Generation: Past, Present and Beyond. arXiv 2018 paper bib

    Sidi Lu, Yaoming Zhu, Weinan Zhang, Jun Wang, Yong Yu

  17. Quiz-Style Question Generation for News Stories. WWW 2021 paper bib

    Ádám D. Lelkes, Vinh Q. Tran, Cong Yu

  18. Recent Advances in Neural Question Generation. arXiv 2019 paper bib

    Liangming Pan, Wenqiang Lei, Tat-Seng Chua, Min-Yen Kan

  19. Recent Advances in SQL Query Generation: A Survey. arXiv 2020 paper bib

    Jovan Kalajdjieski, Martina Toshevska, Frosina Stojanovska

  20. Survey of Hallucination in Natural Language Generation. arXiv 2022 paper bib

    Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Yejin Bang, Andrea Madotto, Pascale Fung

  21. Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation. J. Artif. Intell. Res. 2018 paper bib

    Albert Gatt, Emiel Krahmer

  1. A Review on Fact Extraction and Verification. ACM Comput. Surv. 2023 paper bib

    Giannis Bekoulis, Christina Papagiannopoulou, Nikos Deligiannis

  2. A Survey of Deep Learning Methods for Relation Extraction. arXiv 2017 paper bib

    Shantanu Kumar

  3. A Survey of Event Extraction From Text. IEEE Access 2019 paper bib

    Wei Xiang, Bang Wang

  4. A Survey of event extraction methods from text for decision support systems. Decis. Support Syst. 2016 paper bib

    Frederik Hogenboom, Flavius Frasincar, Uzay Kaymak, Franciska de Jong, Emiel Caron

  5. A survey of joint intent detection and slot-filling models in natural language understanding. arXiv 2021 paper bib

    Henry Weld, Xiaoqi Huang, Siqi Long, Josiah Poon, Soyeon Caren Han

  6. A Survey of Textual Event Extraction from Social Networks. LPKM 2017 paper bib

    Mohamed Mejri, Jalel Akaichi

  7. A Survey on Deep Learning Event Extraction: Approaches and Applications. arXiv 2021 paper bib

    Qian Li, Jianxin Li, Jiawei Sheng, Shiyao Cui, Jia Wu, Yiming Hei, Hao Peng, Shu Guo, Lihong Wang, Amin Beheshti, Philip S. Yu

  8. A Survey on Open Information Extraction. COLING 2018 paper bib

    Christina Niklaus, Matthias Cetto, André Freitas, Siegfried Handschuh

  9. A Survey on Temporal Reasoning for Temporal Information Extraction from Text (Extended Abstract). IJCAI 2020 paper bib

    Artuur Leeuwenberg, Marie-Francine Moens

  10. An Overview of Event Extraction from Text. DeRiVE@ISWC 2011 paper bib

    Frederik Hogenboom, Flavius Frasincar, Uzay Kaymak, Franciska de Jong

  11. Automatic Extraction of Causal Relations from Natural Language Texts: A Comprehensive Survey. arXiv 2016 paper bib

    Nabiha Asghar

  12. Complex Relation Extraction: Challenges and Opportunities. arXiv 2020 paper bib

    Haiyun Jiang, Qiaoben Bao, Qiao Cheng, Deqing Yang, Li Wang, Yanghua Xiao

  13. Extracting Events and Their Relations from Texts: A Survey on Recent Research Progress and Challenges. AI Open 2020 paper bib

    Kang Liu, Yubo Chen, Jian Liu, Xinyu Zuo, Jun Zhao

  14. Knowledge Extraction in Low-Resource Scenarios: Survey and Perspective. arXiv 2022 paper bib

    Shumin Deng, Ningyu Zhang, Hui Chen, Feiyu Xiong, Jeff Z. Pan, Huajun Chen

  15. More Data, More Relations, More Context and More Openness: A Review and Outlook for Relation Extraction. AACL 2020 paper bib

    Xu Han, Tianyu Gao, Yankai Lin, Hao Peng, Yaoliang Yang, Chaojun Xiao, Zhiyuan Liu, Peng Li, Jie Zhou, Maosong Sun

  16. Neural relation extraction: a survey. arXiv 2020 paper bib

    Mehmet Aydar, Ozge Bozal, Furkan Özbay

  17. No Pattern, No Recognition: a Survey about Reproducibility and Distortion Issues of Text Clustering and Topic Modeling. arXiv 2022 paper bib

    Marília Costa Rosendo Silva, Felipe Alves Siqueira, João Pedro Mantovani Tarrega, João Vitor Pataca Beinotti, Augusto Sousa Nunes, Miguel de Mattos Gardini, Vinícius Adolfo Pereira da Silva, Nádia Félix Felipe da Silva, André Carlos Ponce de Leon Ferreira de Carvalho

  18. Recent Neural Methods on Slot Filling and Intent Classification for Task-Oriented Dialogue Systems: A Survey. COLING 2020 paper bib

    Samuel Louvan, Bernardo Magnini

  19. Relation Extraction : A Survey. arXiv 2017 paper bib

    Sachin Pawar, Girish K. Palshikar, Pushpak Bhattacharyya

  20. Techniques for Jointly Extracting Entities and Relations: A Survey. CICLing 2019 paper bib

    Sachin Pawar, Pushpak Bhattacharyya, Girish K. Palshikar

  1. A Brief Survey of Text Mining: Classification, Clustering and Extraction Techniques. arXiv 2017 paper bib

    Mehdi Allahyari, Seyed Amin Pouriyeh, Mehdi Assefi, Saied Safaei, Elizabeth D. Trippe, Juan B. Gutierrez, Krys J. Kochut

  2. A survey of methods to ease the development of highly multilingual text mining applications. Lang. Resour. Evaluation 2012 paper bib

    Ralf Steinberger

  3. A Survey on Retrieval-Augmented Text Generation. arXiv 2022 paper bib

    Huayang Li, Yixuan Su, Deng Cai, Yan Wang, Lemao Liu

  4. Data Mining and Information Retrieval in the 21st century: A bibliographic review. Comput. Sci. Rev. 2019 paper bib

    Jiaying Liu, Xiangjie Kong, Xinyu Zhou, Lei Wang, Da Zhang, Ivan Lee, Bo Xu, Feng Xia

  5. Dense Text Retrieval based on Pretrained Language Models: A Survey. arXiv 2022 paper bib

    Wayne Xin Zhao, Jing Liu, Ruiyang Ren, Ji-Rong Wen

  6. Neural Entity Linking: A Survey of Models Based on Deep Learning. Semantic Web 2022 paper bib

    Özge Sevgili, Artem Shelmanov, Mikhail Y. Arkhipov, Alexander Panchenko, Chris Biemann

  7. Neural Models for Information Retrieval. arXiv 2017 paper bib

    Bhaskar Mitra, Nick Craswell

  8. Opinion Mining and Analysis: A survey. arXiv 2013 paper bib

    Arti Buche, M. B. Chandak, Akshay Zadgaonkar

  9. Pre-training Methods in Information Retrieval. Found. Trends Inf. Retr. 2022 paper bib

    Yixing Fan, Xiaohui Xie, Yinqiong Cai, Jia Chen, Xinyu Ma, Xiangsheng Li, Ruqing Zhang, Jiafeng Guo

  10. Relational World Knowledge Representation in Contextual Language Models: A Review. EMNLP 2021 paper bib

    Tara Safavi, Danai Koutra

  11. Short Text Topic Modeling Techniques, Applications, and Performance: A Survey. IEEE Trans. Knowl. Data Eng. 2022 paper bib

    Jipeng Qiang, Zhenyu Qian, Yun Li, Yunhao Yuan, Xindong Wu

  12. Taking Search to Task. arXiv 2023 paper bib

    Chirag Shah, Ryen W. White, Paul Thomas, Bhaskar Mitra, Shawon Sarkar, Nicholas J. Belkin

  13. Topic Modelling Meets Deep Neural Networks: A Survey. IJCAI 2021 paper bib

    He Zhao, Dinh Q. Phung, Viet Huynh, Yuan Jin, Lan Du, Wray L. Buntine

  1. A Primer in BERTology: What we know about how BERT works. Trans. Assoc. Comput. Linguistics 2020 paper bib

    Anna Rogers, Olga Kovaleva, Anna Rumshisky

  2. A Survey of the State of Explainable AI for Natural Language Processing. AACL 2020 paper bib

    Marina Danilevsky, Kun Qian, Ranit Aharonov, Yannis Katsis, Ban Kawas, Prithviraj Sen

  3. A Survey on Deep Learning and Explainability for Automatic Report Generation from Medical Images. ACM Comput. Surv. 2022 paper bib

    Pablo Messina, Pablo Pino, Denis Parra, Alvaro Soto, Cecilia Besa, Sergio Uribe, Marcelo E. Andia, Cristian Tejos, Claudia Prieto, Daniel Capurro

  4. A Survey on Explainability in Machine Reading Comprehension. arXiv 2020 paper bib

    Mokanarangan Thayaparan, Marco Valentino, André Freitas

  5. Analysis Methods in Neural Language Processing: A Survey. Trans. Assoc. Comput. Linguistics 2019 paper bib

    Yonatan Belinkov, James R. Glass

  6. Analyzing and Interpreting Neural Networks for NLP: A Report on the First BlackboxNLP Workshop. Nat. Lang. Eng. 2019 paper bib

    Afra Alishahi, Grzegorz Chrupala, Tal Linzen

  7. Neuron-level Interpretation of Deep NLP Models: A Survey. Trans. Assoc. Comput. Linguistics 2022 paper bib

    Hassan Sajjad, Nadir Durrani, Fahim Dalvi

  8. Post-hoc Interpretability for Neural NLP: A Survey. ACM Comput. Surv. 2023 paper bib

    Andreas Madsen, Siva Reddy, Sarath Chandar

  9. Teach Me to Explain: A Review of Datasets for Explainable Natural Language Processing. NeurIPS Datasets and Benchmarks 2021 paper bib

    Sarah Wiegreffe, Ana Marasovic

  10. *Which BERT? A Survey Organizing Contextualized Encoders. EMNLP 2020 paper bib

    Patrick Xia, Shijie Wu, Benjamin Van Durme

  1. A Review of Relational Machine Learning for Knowledge Graphs. Proc. IEEE 2016 paper bib

    Maximilian Nickel, Kevin Murphy, Volker Tresp, Evgeniy Gabrilovich

  2. A survey of embedding models of entities and relationships for knowledge graph completion. arXiv 2017 paper bib

    Dat Quoc Nguyen

  3. A Survey of Embedding Space Alignment Methods for Language and Knowledge Graphs. arXiv 2020 paper bib

    Alexander Kalinowski, Yuan An

  4. A Survey of Techniques for Constructing Chinese Knowledge Graphs and Their Applications. Sustainability 2018 paper bib

    Tianxing Wu, Guilin Qi, Cheng Li, Meng Wang

  5. A Survey on Graph Neural Networks for Knowledge Graph Completion. arXiv 2020 paper bib

    Siddhant Arora

  6. A Survey on Knowledge Graphs: Representation, Acquisition and Applications. arXiv 2020 paper bib

    Shaoxiong Ji, Shirui Pan, Erik Cambria, Pekka Marttinen, Philip S. Yu

  7. Introduction to neural network-based question answering over knowledge graphs. WIREs Data Mining Knowl. Discov. 2021 paper bib

    Nilesh Chakraborty, Denis Lukovnikov, Gaurav Maheshwari, Priyansh Trivedi, Jens Lehmann, Asja Fischer

  8. Knowledge Graph Embedding for Link Prediction: A Comparative Analysis. ACM Trans. Knowl. Discov. Data 2021 paper bib

    Andrea Rossi, Denilson Barbosa, Donatella Firmani, Antonio Matinata, Paolo Merialdo

  9. Knowledge Graph Embedding: A Survey from the Perspective of Representation Spaces. arXiv 2022 paper bib

    Jiahang Cao, Jinyuan Fang, Zaiqiao Meng, Shangsong Liang

  10. Knowledge Graph Embedding: A Survey of Approaches and Applications. IEEE Trans. Knowl. Data Eng. 2017 paper bib

    Quan Wang, Zhendong Mao, Bin Wang, Li Guo

  11. Knowledge Graph Refinement: A Survey of Approaches and Evaluation Methods. Semantic Web 2017 paper bib

    Heiko Paulheim

  12. Knowledge Graphs. ACM Comput. Surv. 2021 paper bib

    Aidan Hogan, Eva Blomqvist, Michael Cochez, Claudia d'Amato, Gerard de Melo, Claudio Gutiérrez, Sabrina Kirrane, José Emilio Labra Gayo, Roberto Navigli, Sebastian Neumaier, Axel-Cyrille Ngonga Ngomo, Axel Polleres, Sabbir M. Rashid, Anisa Rula, Lukas Schmelzeisen, Juan Sequeda, Steffen Staab, Antoine Zimmermann

  13. Knowledge Graphs: An Information Retrieval Perspective. Found. Trends Inf. Retr. 2020 paper bib

    Ridho Reinanda, Edgar Meij, Maarten de Rijke

  14. Multi-Modal Knowledge Graph Construction and Application: A Survey. arXiv 2022 paper bib

    Xiangru Zhu, Zhixu Li, Xiaodan Wang, Xueyao Jiang, Penglei Sun, Xuwu Wang, Yanghua Xiao, Nicholas Jing Yuan

  15. Neural, Symbolic and Neural-symbolic Reasoning on Knowledge Graphs. AI Open 2021 paper bib

    Jing Zhang, Bo Chen, Lingxi Zhang, Xirui Ke, Haipeng Ding

  16. Survey and Open Problems in Privacy Preserving Knowledge Graph: Merging, Query, Representation, Completion and Applications. arXiv 2020 paper bib

    Chaochao Chen, Jamie Cui, Guanfeng Liu, Jia Wu, Li Wang

  17. The Contribution of Knowledge in Visiolinguistic Learning: A Survey on Tasks and Challenges. arXiv 2023 paper bib

    Maria Lymperaiou, Giorgos Stamou

  1. A comprehensive survey of mostly textual document segmentation algorithms since 2008. Pattern Recognit. 2017 paper bib

    Sébastien Eskenazi, Petra Gomez-Krämer, Jean-Marc Ogier

  2. Emotionally-Aware Chatbots: A Survey. arXiv 2019 paper bib

    Endang Wahyu Pamungkas

  3. From Show to Tell: A Survey on Deep Learning-based Image Captioning. IEEE Trans. Pattern Anal. Mach. Intell. 2023 paper bib

    Matteo Stefanini, Marcella Cornia, Lorenzo Baraldi, Silvia Cascianelli, Giuseppe Fiameni, Rita Cucchiara

  4. Trends in Integration of Vision and Language Research: A Survey of Tasks, Datasets, and Methods. J. Artif. Intell. Res. 2021 paper bib

    Aditya Mogadala, Marimuthu Kalimuthu, Dietrich Klakow

  1. A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT. arXiv 2023 paper bib

    Yihan Cao, Siyu Li, Yixin Liu, Zhiling Yan, Yutong Dai, Philip S. Yu, Lichao Sun

  2. A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT. arXiv 2023 paper bib

    Ce Zhou, Qian Li, Chen Li, Jun Yu, Yixin Liu, Guangjing Wang, Kai Zhang, Cheng Ji, Qiben Yan, Lifang He, Hao Peng, Jianxin Li, Jia Wu, Ziwei Liu, Pengtao Xie, Caiming Xiong, Jian Pei, Philip S. Yu, Lichao Sun

  3. A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation. arXiv 2023 paper bib

    Xiaowei Huang, Wenjie Ruan, Wei Huang, Gaojie Jin, Yi Dong, Changshun Wu, Saddek Bensalem, Ronghui Mu, Yi Qi, Xingyu Zhao, Kaiwen Cai, Yanghao Zhang, Sihao Wu, Peipei Xu, Dengyu Wu, Andre Freitas, Mustafa A. Mustafa

  4. A Survey on In-context Learning. arXiv 2023 paper bib

    Qingxiu Dong, Lei Li, Damai Dai, Ce Zheng, Zhiyong Wu, Baobao Chang, Xu Sun, Jingjing Xu, Lei Li, Zhifang Sui

  5. A Survey of Large Language Models. arXiv 2023 paper bib

    Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, Yifan Du, Chen Yang, Yushuo Chen, Zhipeng Chen, Jinhao Jiang, Ruiyang Ren, Yifan Li, Xinyu Tang, Zikang Liu, Peiyu Liu, Jian-Yun Nie, Ji-Rong Wen

  6. AI-Augmented Surveys: Leveraging Large Language Models for Opinion Prediction in Nationally Representative Surveys. arXiv 2023 paper bib

    Junsol Kim, Byungkyu Lee

  7. Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation. arXiv 2023 paper bib

    Patrick Fernandes, Aman Madaan, Emmy Liu, António Farinhas, Pedro Henrique Martins, Amanda Bertsch, José G. C. de Souza, Shuyan Zhou, Tongshuang Wu, Graham Neubig, André F. T. Martins

  8. Eight Things to Know about Large Language Models. arXiv 2023 paper bib

    Samuel R. Bowman

  9. Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond. arXiv 2023 paper bib

    Jingfeng Yang, Hongye Jin, Ruixiang Tang, Xiaotian Han, Qizhang Feng, Haoming Jiang, Bing Yin, Xia Hu

  10. Language Model Behavior: A Comprehensive Survey. arXiv 2023 paper bib

    Tyler A. Chang, Benjamin K. Bergen

  11. Large Language Models Meet NL2Code: A Survey. arXiv 2023 paper bib

    Daoguang Zan, Bei Chen, Fengji Zhang, Dianjie Lu, Bingchao Wu, Bei Guan, Yongji Wang, Jian-Guang Lou

  12. Large-scale Multi-Modal Pre-trained Models: A Comprehensive Survey. arXiv 2023 paper bib

    Xiao Wang, Guangyao Chen, Guangwu Qian, Pengcheng Gao, Xiao-Yong Wei, Yaowei Wang, Yonghong Tian, Wen Gao

  13. On Efficient Training of Large-Scale Deep Learning Models: A Literature Review. arXiv 2023 paper bib

    Li Shen, Yan Sun, Zhiyuan Yu, Liang Ding, Xinmei Tian, Dacheng Tao

  14. One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC Era. arXiv 2023 paper bib

    Chaoning Zhang, Chenshuang Zhang, Chenghao Li, Yu Qiao, Sheng Zheng, Sumit Kumar Dam, Mengchun Zhang, Jung Uk Kim, Seong Tae Kim, Jinwoo Choi, Gyeong-Moon Park, Sung-Ho Bae, Lik-Hang Lee, Pan Hui, In So Kweon, Choong Seon Hong

  15. Perception, performance, and detectability of conversational artificial intelligence across 32 university courses. arXiv 2023 paper bib

    Hazem Ibrahim, Fengyuan Liu, Rohail Asim, Balaraju Battu, Sidahmed Benabderrahmane, Bashar Alhafni, Wifag Adnan, Tuka Alhanai, Bedoor AlShebli, Riyadh Baghdadi, Jocelyn J. Bélanger, Elena Beretta, Kemal Celik, Moumena Chaqfeh, Mohammed F. Daqaq, Zaynab El Bernoussi, Daryl Fougnie, Borja Garcia de Soto, Alberto Gandolfi, Andras Gyorgy, Nizar Habash, J. Andrew Harris, Aaron Kaufman, Lefteris Kirousis, Korhan Kocak

  16. Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey. arXiv 2021 paper bib

    Bonan Min, Hayley Ross, Elior Sulem, Amir Pouran Ben Veyseh, Thien Huu Nguyen, Oscar Sainz, Eneko Agirre, Ilana Heintz, Dan Roth

  17. Shortcut Learning of Large Language Models in Natural Language Understanding: A Survey. arXiv 2022 paper bib

    Mengnan Du, Fengxiang He, Na Zou, Dacheng Tao, Xia Hu

  18. Summary of ChatGPT/GPT-4 Research and Perspective Towards the Future of Large Language Models. arXiv 2023 paper bib

    Yiheng Liu, Tianle Han, Siyuan Ma, Jiayue Zhang, Yuanyuan Yang, Jiaming Tian, Hao He, Antong Li, Mengshen He, Zhengliang Liu, Zihao Wu, Dajiang Zhu, Xiang Li, Ning Qiang, Dingang Shen, Tianming Liu, Bao Ge

  19. The Contribution of Knowledge in Visiolinguistic Learning: A Survey on Tasks and Challenges. arXiv 2023 paper bib

    Maria Lymperaiou, Giorgos Stamou

  20. The Science of Detecting LLM-Generated Texts. arXiv 2023 paper bib

    Ruixiang Tang, Yu-Neng Chuang, Xia Hu

  21. The Shaky Foundations of Clinical Foundation Models: A Survey of Large Language Models and Foundation Models for EMRs. arXiv 2023 paper bib

    Michael Wornow, Yizhe Xu, Rahul Thapa, Birju S. Patel, Ethan Steinberg, Scott L. Fleming, Michael A. Pfeffer, Jason A. Fries, Nigam H. Shah

  22. Towards Reasoning in Large Language Models: A Survey. arXiv 2022 paper bib

    Jie Huang, Kevin Chen-Chuan Chang

  23. Tricking LLMs into Disobedience: Understanding, Analyzing, and Preventing Jailbreaks. arXiv 2023 paper bib

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  18. The Factual Inconsistency Problem in Abstractive Text Summarization: A Survey. arXiv 2021 paper bib

    Yi-Chong Huang, Xia-Chong Feng, Xiao-Cheng Feng, Bing Qin

  19. What Have We Achieved on Text Summarization?. EMNLP 2020 paper bib

    Dandan Huang, Leyang Cui, Sen Yang, Guangsheng Bao, Kun Wang, Jun Xie, Yue Zhang

  1. A survey of cross-lingual features for zero-shot cross-lingual semantic parsing. arXiv 2019 paper bib

    Jingfeng Yang, Federico Fancellu, Bonnie L. Webber

  2. A Survey of Syntactic-Semantic Parsing Based on Constituent and Dependency Structures. arXiv 2020 paper bib

    Meishan Zhang

  3. A Survey on Recent Advances in Sequence Labeling from Deep Learning Models. arXiv 2020 paper bib

    Zhiyong He, Zanbo Wang, Wei Wei, Shanshan Feng, Xianling Mao, Sheng Jiang

  4. A Survey on Semantic Parsing. AKBC 2019 paper bib

    Aishwarya Kamath, Rajarshi Das

  5. A Survey on Semantic Parsing from the perspective of Compositionality. arXiv 2020 paper bib

    Pawan Kumar, Srikanta Bedathur

  6. A Survey on Text-to-SQL Parsing: Concepts, Methods, and Future Directions. arXiv 2022 paper bib

    Bowen Qin, Binyuan Hui, Lihan Wang, Min Yang, Jinyang Li, Binhua Li, Ruiying Geng, Rongyu Cao, Jian Sun, Luo Si, Fei Huang, Yongbin Li

  7. Context Dependent Semantic Parsing: A Survey. COLING 2020 paper bib

    Zhuang Li, Lizhen Qu, Gholamreza Haffari

  8. Design Challenges and Misconceptions in Neural Sequence Labeling. COLING 2018 paper bib

    Jie Yang, Shuailong Liang, Yue Zhang

  9. Part‐of‐speech tagging. Wiley Interdisciplinary Reviews: Computational Statistics 2011 paper bib

    Angel R. Martinez

  10. Sememe knowledge computation: a review of recent advances in application and expansion of sememe knowledge bases. Frontiers Comput. Sci. 2021 paper bib

    Fanchao Qi, Ruobing Xie, Yuan Zang, Zhiyuan Liu, Maosong Sun

  11. Syntactic Parsing: A Survey. Computers and the Humanities 1989 paper bib

    Alton F. Sanders and Ruth H. Sanders

  12. Syntax Representation in Word Embeddings and Neural Networks - A Survey. ITAT 2020 paper bib

    Tomasz Limisiewicz, David Marecek

  13. The Gap of Semantic Parsing: A Survey on Automatic Math Word Problem Solvers. IEEE Trans. Pattern Anal. Mach. Intell. 2020 paper bib

    Dongxiang Zhang, Lei Wang, Luming Zhang, Bing Tian Dai, Heng Tao Shen

  1. A Survey of Active Learning for Text Classification using Deep Neural Networks. arXiv 2020 paper bib

    Christopher Schröder, Andreas Niekler

  2. A Survey of Naïve Bayes Machine Learning approach in Text Document Classification. arXiv 2010 paper bib

    K. A. Vidhya, G. Aghila

  3. A Survey on Data Augmentation for Text Classification. ACM Comput. Surv. 2023 paper bib

    Markus Bayer, Marc-André Kaufhold, Christian Reuter

  4. A Survey on Natural Language Processing for Fake News Detection. LREC 2020 paper bib

    Ray Oshikawa, Jing Qian, William Yang Wang

  5. A survey on phrase structure learning methods for text classification. arXiv 2014 paper bib

    Reshma Prasad, Mary Priya Sebastian

  6. A Survey on Stance Detection for Mis- and Disinformation Identification. NAACL-HLT 2022 paper bib

    Momchil Hardalov, Arnav Arora, Preslav Nakov, Isabelle Augenstein

  7. A Survey on Text Classification: From Shallow to Deep Learning. arXiv 2020 paper bib

    Qian Li, Hao Peng, Jianxin Li, Congying Xia, Renyu Yang, Lichao Sun, Philip S. Yu, Lifang He

  8. Automatic Language Identification in Texts: A Survey. J. Artif. Intell. Res. 2019 paper bib

    Tommi Jauhiainen, Marco Lui, Marcos Zampieri, Timothy Baldwin, Krister Lindén

  9. Deep Learning-based Text Classification: A Comprehensive Review. ACM Comput. Surv. 2022 paper bib

    Shervin Minaee, Nal Kalchbrenner, Erik Cambria, Narjes Nikzad, Meysam Chenaghlu, Jianfeng Gao

  10. Fake News Detection using Stance Classification: A Survey. arXiv 2019 paper bib

    Anders Edelbo Lillie, Emil Refsgaard Middelboe

  11. Out-of-Distribution Generalization in Text Classification: Past, Present, and Future. arXiv 2023 paper bib

    Linyi Yang, Yaoxiao Song, Xuan Ren, Chenyang Lyu, Yidong Wang, Lingqiao Liu, Jindong Wang, Jennifer Foster, Yue Zhang

  12. Semantic text classification: A survey of past and recent advances. Inf. Process. Manag. 2018 paper bib

    Berna Altinel, Murat Can Ganiz

  13. Text Classification Algorithms: A Survey. Inf. 2019 paper bib

    Kamran Kowsari, Kiana Jafari Meimandi, Mojtaba Heidarysafa, Sanjana Mendu, Laura E. Barnes, Donald E. Brown

The ML Paper List

  1. A General Survey on Attention Mechanisms in Deep Learning. arXiv 2022 paper bib

    Gianni Brauwers, Flavius Frasincar

  2. A Practical Survey on Faster and Lighter Transformers. arXiv 2021 paper bib

    Quentin Fournier, Gaétan Marceau Caron, Daniel Aloise

  3. A Review of Binarized Neural Networks. Electronics 2019 paper bib

    Taylor Simons, Dah-Jye Lee

  4. A Review of Sparse Expert Models in Deep Learning. arXiv 2022 paper bib

    William Fedus, Jeff Dean, Barret Zoph

  5. A State-of-the-Art Survey on Deep Learning Theory and Architectures. Electronics 2019 paper bib

    Md Zahangir Alom, Tarek M. Taha, Chris Yakopcic, Stefan Westberg, Paheding Sidike, Mst Shamima Nasrin, Mahmudul Hasan, Brian C. Van Essen, Abdul A. S. Awwal and Vijayan K. Asari

  6. A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects. arXiv 2020 paper bib

    Zewen Li, Wenjie Yang, Shouheng Peng, Fan Liu

  7. A Survey of End-to-End Driving: Architectures and Training Methods. arXiv 2020 paper bib

    Ardi Tampuu, Maksym Semikin, Naveed Muhammad, Dmytro Fishman, Tambet Matiisen

  8. A survey of the recent architectures of deep convolutional neural networks. Artif. Intell. Rev. 2020 paper bib

    Asifullah Khan, Anabia Sohail, Umme Zahoora, Aqsa Saeed Qureshi

  9. A Survey of Transformers. AI Open 2022 paper bib

    Tianyang Lin, Yuxin Wang, Xiangyang Liu, Xipeng Qiu

  10. A Survey on Activation Functions and their relation with Xavier and He Normal Initialization. arXiv 2020 paper bib

    Leonid Datta

  11. A Survey on Latent Tree Models and Applications. J. Artif. Intell. Res. 2013 paper bib

    Raphaël Mourad, Christine Sinoquet, Nevin Lianwen Zhang, Tengfei Liu, Philippe Leray

  12. A survey on modern trainable activation functions. Neural Networks 2021 paper bib

    Andrea Apicella, Francesco Donnarumma, Francesco Isgrò, Roberto Prevete

  13. A Survey on Vision Transformer. IEEE Trans. Pattern Anal. Mach. Intell. 2023 paper bib

    Kai Han, Yunhe Wang, Hanting Chen, Xinghao Chen, Jianyuan Guo, Zhenhua Liu, Yehui Tang, An Xiao, Chunjing Xu, Yixing Xu, Zhaohui Yang, Yiman Zhang, Dacheng Tao

  14. An Attentive Survey of Attention Models. ACM Trans. Intell. Syst. Technol. 2021 paper bib

    Sneha Chaudhari, Varun Mithal, Gungor Polatkan, Rohan Ramanath

  15. An Introduction to Autoencoders. arXiv 2022 paper bib

    Umberto Michelucci

  16. Attention mechanisms and deep learning for machine vision: A survey of the state of the art. arXiv 2021 paper bib

    Abdul Mueed Hafiz, Shabir Ahmad Parah, Rouf Ul Alam Bhat

  17. Attention Mechanisms in Computer Vision: A Survey. Comput. Vis. Media 2022 paper bib

    Meng-Hao Guo, Tian-Xing Xu, Jiang-Jiang Liu, Zheng-Ning Liu, Peng-Tao Jiang, Tai-Jiang Mu, Song-Hai Zhang, Ralph R. Martin, Ming-Ming Cheng, Shi-Min Hu

  18. Big Networks: A Survey. Comput. Sci. Rev. 2020 paper bib

    Hayat Dino Bedru, Shuo Yu, Xinru Xiao, Da Zhang, Liangtian Wan, He Guo, Feng Xia

  19. Binary Neural Networks: A Survey. Pattern Recognit. 2020 paper bib

    Haotong Qin, Ruihao Gong, Xianglong Liu, Xiao Bai, Jingkuan Song, Nicu Sebe

  20. Deep Echo State Network (DeepESN): A Brief Survey. arXiv 2017 paper bib

    Claudio Gallicchio, Alessio Micheli

  21. Deep Tree Transductions - A Short Survey. INNSBDDL 2019 paper bib

    Davide Bacciu, Antonio Bruno

  22. Efficient Transformers: A Survey. ACM Comput. Surv. 2023 paper bib

    Yi Tay, Mostafa Dehghani, Dara Bahri, Donald Metzler

  23. Learning with Capsules: A Survey. arXiv 2022 paper bib

    Fabio De Sousa Ribeiro, Kevin Duarte, Miles Everett, Georgios Leontidis, Mubarak Shah

  24. On the Opportunity of Causal Deep Generative Models: A Survey and Future Directions. arXiv 2023 paper bib

    Guanglin Zhou, Lina Yao, Xiwei Xu, Chen Wang, Liming Zhu, Kun Zhang

  25. Pooling Methods in Deep Neural Networks, a Review. arXiv 2020 paper bib

    Hossein Gholamalinezhad, Hossein Khosravi

  26. Position Information in Transformers: An Overview. Comput. Linguistics 2022 paper bib

    Philipp Dufter, Martin Schmitt, Hinrich Schütze

  27. Recent Advances in Convolutional Neural Networks. Pattern Recognit. 2018 paper bib

    Jiuxiang Gu, Zhenhua Wang, Jason Kuen, Lianyang Ma, Amir Shahroudy, Bing Shuai, Ting Liu, Xingxing Wang, Gang Wang, Jianfei Cai, Tsuhan Chen

  28. Sum-Product Networks: A Survey. arXiv 2020 paper bib

    Iago París, Raquel Sánchez-Cauce, Francisco Javier Díez

  29. Survey of Dropout Methods for Deep Neural Networks. arXiv 2019 paper bib

    Alex Labach, Hojjat Salehinejad, Shahrokh Valaee

  30. Survey on the attention based RNN model and its applications in computer vision. arXiv 2016 paper bib

    Feng Wang, David M. J. Tax

  31. The History Began from AlexNet: A Comprehensive Survey on Deep Learning Approaches. arXiv 2018 paper bib

    Md. Zahangir Alom, Tarek M. Taha, Christopher Yakopcic, Stefan Westberg, Paheding Sidike, Mst Shamima Nasrin, Brian C. Van Essen, Abdul A. S. Awwal, Vijayan K. Asari

  32. The NLP Cookbook: Modern Recipes for Transformer based Deep Learning Architectures. IEEE Access 2021 paper bib

    Sushant Singh, Ausif Mahmood

  33. Transformers in Vision: A Survey. ACM Comput. Surv. 2022 paper bib

    Salman H. Khan, Muzammal Naseer, Munawar Hayat, Syed Waqas Zamir, Fahad Shahbaz Khan, Mubarak Shah

  34. Understanding LSTM - a tutorial into Long Short-Term Memory Recurrent Neural Networks. arXiv 2019 paper bib

    Ralf C. Staudemeyer, Eric Rothstein Morris

  1. A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions. ACM Comput. Surv. 2022 paper bib

    Pengzhen Ren, Yun Xiao, Xiaojun Chang, Poyao Huang, Zhihui Li, Xiaojiang Chen, Xin Wang

  2. A Comprehensive Survey on Automated Machine Learning for Recommendations. arXiv 2022 paper bib

    Bo Chen, Xiangyu Zhao, Yejing Wang, Wenqi Fan, Huifeng Guo, Ruiming Tang

  3. A Comprehensive Survey on Hardware-Aware Neural Architecture Search. arXiv 2021 paper bib

    Hadjer Benmeziane, Kaoutar El Maghraoui, Hamza Ouarnoughi, Smaïl Niar, Martin Wistuba, Naigang Wang

  4. A Review of Meta-Reinforcement Learning for Deep Neural Networks Architecture Search. arXiv 2018 paper bib

    Yesmina Jaâfra, Jean Luc Laurent, Aline Deruyver, Mohamed Saber Naceur

  5. A Survey on Neural Architecture Search. arXiv 2019 paper bib

    Martin Wistuba, Ambrish Rawat, Tejaswini Pedapati

  6. Automated Machine Learning on Graphs: A Survey. IJCAI 2021 paper bib

    Ziwei Zhang, Xin Wang, Wenwu Zhu

  7. AutoML for Deep Recommender Systems: A Survey. arXiv 2022 paper bib

    Ruiqi Zheng, Liang Qu, Bin Cui, Yuhui Shi, Hongzhi Yin

  8. AutoML: A Survey of the State-of-the-Art. Knowl. Based Syst. 2021 paper bib

    Xin He, Kaiyong Zhao, Xiaowen Chu

  9. Benchmark and Survey of Automated Machine Learning Frameworks. J. Artif. Intell. Res. 2021 paper bib

    Marc-André Zöller, Marco F. Huber

  10. Neural Architecture Search: A Survey. J. Mach. Learn. Res. 2019 paper bib

    Thomas Elsken, Jan Hendrik Metzen, Frank Hutter

  11. Reinforcement learning for neural architecture search: A review. Image Vis. Comput. 2019 paper bib

    Yesmina Jaâfra, Jean Luc Laurent, Aline Deruyver, Mohamed Saber Naceur

  12. Survey on Evolutionary Deep Learning: Principles, Algorithms, Applications and Open Issues. arXiv 2022 paper bib

    Nan Li, Lianbo Ma, Guo Yu, Bing Xue, Mengjie Zhang, Yaochu Jin

  1. A survey of non-exchangeable priors for Bayesian nonparametric models. IEEE Trans. Pattern Anal. Mach. Intell. 2015 paper bib

    Nicholas J. Foti, Sinead A. Williamson

  2. A Survey on Bayesian Deep Learning. ACM Comput. Surv. 2021 paper bib

    Hao Wang, Dit-Yan Yeung

  3. Bayesian Neural Networks: An Introduction and Survey. arXiv 2020 paper bib

    Ethan Goan, Clinton Fookes

  4. Bayesian Nonparametric Space Partitions: A Survey. IJCAI 2021 paper bib

    Xuhui Fan, Bin Li, Ling Luo, Scott A. Sisson

  5. Deep Bayesian Active Learning, A Brief Survey on Recent Advances. arXiv 2020 paper bib

    Salman Mohamadi, Hamidreza Amindavar

  6. Hands-on Bayesian Neural Networks - a Tutorial for Deep Learning Users. arXiv 2020 paper bib

    Laurent Valentin Jospin, Wray L. Buntine, Farid Boussaïd, Hamid Laga, Mohammed Bennamoun

  7. Taking the Human Out of the Loop: A Review of Bayesian Optimization. Proc. IEEE 2016 paper bib

    Bobak Shahriari, Kevin Swersky, Ziyu Wang, Ryan P. Adams, Nando de Freitas

  1. A continual learning survey: Defying forgetting in classification tasks. IEEE Trans. Pattern Anal. Mach. Intell. 2022 paper bib

    Matthias De Lange, Rahaf Aljundi, Marc Masana, Sarah Parisot, Xu Jia, Ales Leonardis, Gregory G. Slabaugh, Tinne Tuytelaars

  2. A Survey of Classification Techniques in the Area of Big Data. arXiv 2015 paper bib

    Praful Koturwar, Sheetal Girase, Debajyoti Mukhopadhyay

  3. A Survey of Constrained Gaussian Process Regression: Approaches and Implementation Challenges. arXiv 2020 paper bib

    Laura P. Swiler, Mamikon Gulian, Ari Frankel, Cosmin Safta, John D. Jakeman

  4. A Survey of Deep Graph Clustering: Taxonomy, Challenge, and Application. arXiv 2022 paper bib

    Yue Liu, Jun Xia, Sihang Zhou, Siwei Wang, Xifeng Guo, Xihong Yang, Ke Liang, Wenxuan Tu, Stan Z. Li, Xinwang Liu

  5. A Survey of Machine Learning Methods and Challenges for Windows Malware Classification. arXiv 2020 paper bib

    Edward Raff, Charles Nicholas

  6. A Survey of Methods for Managing the Classification and Solution of Data Imbalance Problem. arXiv 2020 paper bib

    Khan Md. Hasib, Md. Sadiq Iqbal, Faisal Muhammad Shah, Jubayer Al Mahmud, Mahmudul Hasan Popel, Md. Imran Hossain Showrov, Shakil Ahmed, Obaidur Rahman

  7. A Survey of Techniques All Classifiers Can Learn from Deep Networks: Models, Optimizations, and Regularization. arXiv 2019 paper bib

    Alireza Ghods, Diane J. Cook

  8. A Survey on Multi-View Clustering. arXiv 2017 paper bib

    Guoqing Chao, Shiliang Sun, Jinbo Bi

  9. Comprehensive Comparative Study of Multi-Label Classification Methods. Expert Syst. Appl. 2022 paper bib

    Jasmin Bogatinovski, Ljupco Todorovski, Saso Dzeroski, Dragi Kocev

  10. Deep Clustering: A Comprehensive Survey. arXiv 2022 paper bib

    Yazhou Ren, Jingyu Pu, Zhimeng Yang, Jie Xu, Guofeng Li, Xiaorong Pu, Philip S. Yu, Lifang He

  11. Deep learning for time series classification: a review. Data Min. Knowl. Discov. 2019 paper bib

    Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, Lhassane Idoumghar, Pierre-Alain Muller

  12. How Complex is your classification problem? A survey on measuring classification complexity. arXiv 2018 paper bib

    Ana Carolina Lorena, Luís Paulo F. Garcia, Jens Lehmann, Marcilio C. P. de Souto, Tin Kam Ho

  1. 3D Human Motion Prediction: A Survey. Neurocomputing 2022 paper bib

    Kedi Lyu, Haipeng Chen, Zhenguang Liu, Beiqi Zhang, Ruili Wang

  2. 3D Object Detection for Autonomous Driving: A Survey. Pattern Recognit. 2022 paper bib

    Rui Qian, Xin Lai, Xirong Li

  3. 3D Object Detection from Images for Autonomous Driving: A Survey. arXiv 2022 paper bib

    Xinzhu Ma, Wanli Ouyang, Andrea Simonelli, Elisa Ricci

  4. 3D Vision with Transformers: A Survey. arXiv 2022 paper bib

    Jean Lahoud, Jiale Cao, Fahad Shahbaz Khan, Hisham Cholakkal, Rao Muhammad Anwer, Salman Khan, Ming-Hsuan Yang

  5. A Survey of Automated Data Augmentation Algorithms for Deep Learning-based Image Classification Tasks. arXiv 2022 paper bib

    Zihan Yang, Richard O. Sinnott, James Bailey, Qiuhong Ke

  6. A Survey of Black-Box Adversarial Attacks on Computer Vision Models. arXiv 2019 paper bib

    Siddhant Bhambri, Sumanyu Muku, Avinash Tulasi, Arun Balaji Buduru

  7. A Survey of Deep Face Restoration: Denoise, Super-Resolution, Deblur, Artifact Removal. arXiv 2022 paper bib

    Tao Wang, Kaihao Zhang, Xuanxi Chen, Wenhan Luo, Jiankang Deng, Tong Lu, Xiaochun Cao, Wei Liu, Hongdong Li, Stefanos Zafeiriou

  8. A survey of loss functions for semantic segmentation. CIBCB 2020 paper bib

    Shruti Jadon

  9. A Survey of Modern Deep Learning based Object Detection Models. Digit. Signal Process. 2022 paper bib

    Syed Sahil Abbas Zaidi, Mohammad Samar Ansari, Asra Aslam, Nadia Kanwal, Mamoona Naveed Asghar, Brian Lee

  10. A survey of top-down approaches for human pose estimation. arXiv 2022 paper bib

    Thong Duy Nguyen, Milan Kresovic

  11. A Survey of Vision-Language Pre-Trained Models. IJCAI 2022 paper bib

    Yifan Du, Zikang Liu, Junyi Li, Wayne Xin Zhao

  12. A Survey of Visual Sensory Anomaly Detection. arXiv 2022 paper bib

    Xi Jiang, Guoyang Xie, Jinbao Wang, Yong Liu, Chengjie Wang, Feng Zheng, Yaochu Jin

  13. A Survey of Visual Transformers. arXiv 2021 paper bib

    Yang Liu, Yao Zhang, Yixin Wang, Feng Hou, Jin Yuan, Jiang Tian, Yang Zhang, Zhongchao Shi, Jianping Fan, Zhiqiang He

  14. A survey on applications of augmented, mixed and virtual reality for nature and environment. HCI 2021 paper bib

    Jason R. Rambach, Gergana Lilligreen, Alexander Schäfer, Ramya Bankanal, Alexander Wiebel, Didier Stricker

  15. A survey on deep hashing for image retrieval. arXiv 2020 paper bib

    Xiaopeng Zhang

  16. A Survey on Deep Learning in Medical Image Analysis. Medical Image Anal. 2017 paper bib

    Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi, Arnaud Arindra Adiyoso Setio, Francesco Ciompi, Mohsen Ghafoorian, Jeroen A. W. M. van der Laak, Bram van Ginneken, Clara I. Sánchez

  17. A Survey on Deep Learning Technique for Video Segmentation. arXiv 2021 paper bib

    Wenguan Wang, Tianfei Zhou, Fatih Porikli, David J. Crandall, Luc Van Gool

  18. A Survey on Graph Neural Networks and Graph Transformers in Computer Vision: A Task-Oriented Perspective. arXiv 2022 paper bib

    Chaoqi Chen, Yushuang Wu, Qiyuan Dai, Hong-Yu Zhou, Mutian Xu, Sibei Yang, Xiaoguang Han, Yizhou Yu

  19. A Survey on Label-efficient Deep Image Segmentation: Bridging the Gap between Weak Supervision and Dense Prediction. IEEE Trans. Pattern Anal. Mach. Intell. 2022 paper bib

    Wei Shen, Zelin Peng, Xuehui Wang, Huayu Wang, Jiazhong Cen, Dongsheng Jiang, Lingxi Xie, Xiaokang Yang, Qi Tian

  20. A Survey on Visual Map Localization Using LiDARs and Cameras. arXiv 2022 paper bib

    Mahdi Elhousni, Xinming Huang

  21. A Technical Survey and Evaluation of Traditional Point Cloud Clustering Methods for LiDAR Panoptic Segmentation. ICCVW 2021 paper bib

    Yiming Zhao, Xiao Zhang, Xinming Huang

  22. Advances in adversarial attacks and defenses in computer vision: A survey. IEEE Access 2021 paper bib

    Naveed Akhtar, Ajmal Mian, Navid Kardan, Mubarak Shah

  23. Adversarial Examples on Object Recognition: A Comprehensive Survey. ACM Comput. Surv. 2021 paper bib

    Alexandru Constantin Serban, Erik Poll, Joost Visser

  24. Adversarial Machine Learning in Image Classification: A Survey Towards the Defender's Perspective. arXiv 2020 paper bib

    Gabriel Resende Machado, Eugênio Silva, Ronaldo Ribeiro Goldschmidt

  25. Affective Image Content Analysis: Two Decades Review and New Perspectives. IEEE Trans. Pattern Anal. Mach. Intell. 2022 paper bib

    Sicheng Zhao, Xingxu Yao, Jufeng Yang, Guoli Jia, Guiguang Ding, Tat-Seng Chua, Björn W. Schuller, Kurt Keutzer

  26. Applications of Artificial Neural Networks in Microorganism Image Analysis: A Comprehensive Review from Conventional Multilayer Perceptron to Popular Convolutional Neural Network and Potential Visual Transformer. arXiv 2021 paper bib

    Jinghua Zhang, Chen Li, Marcin Grzegorzek

  27. Automatic Gaze Analysis: A Survey of Deep Learning based Approaches. arXiv 2021 paper bib

    Shreya Ghosh, Abhinav Dhall, Munawar Hayat, Jarrod Knibbe, Qiang Ji

  28. Bridging Gap between Image Pixels and Semantics via Supervision: A Survey. arXiv 2021 paper bib

    Jiali Duan, C.-C. Jay Kuo

  29. Compositional Scene Representation Learning via Reconstruction: A Survey. arXiv 2022 paper bib

    Jinyang Yuan, Tonglin Chen, Bin Li, Xiangyang Xue

  30. Deep Depth Completion from Extremely Sparse Data: A Survey. IEEE Trans. Pattern Anal. Mach. Intell. 2022 paper bib

    Junjie Hu, Chenyu Bao, Mete Ozay, Chenyou Fan, Qing Gao, Honghai Liu, Tin Lun Lam

  31. Deep Image Deblurring: A Survey. Int. J. Comput. Vis. 2022 paper bib

    Kaihao Zhang, Wenqi Ren, Wenhan Luo, Wei-Sheng Lai, Björn Stenger, Ming-Hsuan Yang, Hongdong Li

  32. Deep Learning for 3D Point Cloud Understanding: A Survey. arXiv 2020 paper bib

    Haoming Lu, Humphrey Shi

  33. Deep Learning for Embodied Vision Navigation: A Survey. arXiv 2021 paper bib

    Fengda Zhu, Yi Zhu, Xiaodan Liang, Xiaojun Chang

  34. Deep Learning for Image Super-resolution: A Survey. IEEE Trans. Pattern Anal. Mach. Intell. 2021 paper bib

    Zhihao Wang, Jian Chen, Steven C. H. Hoi

  35. Deep Learning for Instance Retrieval: A Survey. IEEE Trans. Pattern Anal. Mach. Intell. 2021 paper bib

    Wei Chen, Yu Liu, Weiping Wang, Erwin Bakker, Theodoros Georgiou, Paul Fieguth, Li Liu, Michael S. Lew

  36. Deep Learning for Scene Classification: A Survey. arXiv 2021 paper bib

    Delu Zeng, Minyu Liao, Mohammad Tavakolian, Yulan Guo, Bolei Zhou, Dewen Hu, Matti Pietikäinen, Li Liu

  37. Deep Learning Technique for Human Parsing: A Survey and Outlook. arXiv 2023 paper bib

    Lu Yang, Wenhe Jia, Shan Li, Qing Song

  38. Efficient High-Resolution Deep Learning: A Survey. arXiv 2022 paper bib

    Arian Bakhtiarnia, Qi Zhang, Alexandros Iosifidis

  39. Geometric and Learning-based Mesh Denoising: A Comprehensive Survey. arXiv 2022 paper bib

    Honghua Chen, Mingqiang Wei, Jun Wang

  40. Image Segmentation Using Deep Learning: A Survey. IEEE Trans. Pattern Anal. Mach. Intell. 2022 paper bib

    Shervin Minaee, Yuri Boykov, Fatih Porikli, Antonio Plaza, Nasser Kehtarnavaz, Demetri Terzopoulos

  41. Image/Video Deep Anomaly Detection: A Survey. arXiv 2021 paper bib

    Bahram Mohammadi, Mahmood Fathy, Mohammad Sabokrou

  42. Image-to-Image Translation: Methods and Applications. IEEE Trans. Multim. 2022 paper bib

    Yingxue Pang, Jianxin Lin, Tao Qin, Zhibo Chen

  43. Imbalance Problems in Object Detection: A Review. IEEE Trans. Pattern Anal. Mach. Intell. 2021 paper bib

    Kemal Oksuz, Baris Can Cam, Sinan Kalkan, Emre Akbas

  44. MmWave Radar and Vision Fusion for Object Detection in Autonomous Driving: A Review. Sensors 2022 paper bib

    Zhiqing Wei, Fengkai Zhang, Shuo Chang, Yangyang Liu, Huici Wu, Zhiyong Feng

  45. Multi-modal Sensor Fusion for Auto Driving Perception: A Survey. arXiv 2022 paper bib

    Keli Huang, Botian Shi, Xiang Li, Xin Li, Siyuan Huang, Yikang Li

  46. Object Detection in 20 Years: A Survey. arXiv 2019 paper bib

    Zhengxia Zou, Zhenwei Shi, Yuhong Guo, Jieping Ye

  47. Recent Advances in Vision Transformer: A Survey and Outlook of Recent Work. arXiv 2022 paper bib

    Khawar Islam

  48. Recovering 3D Human Mesh from Monocular Images: A Survey. arXiv 2022 paper bib

    Yating Tian, Hongwen Zhang, Yebin Liu, Limin Wang

  49. Single Image Super-Resolution Methods: A Survey. arXiv 2022 paper bib

    Bahattin Can Maral

  50. Temporal Sentence Grounding in Videos: A Survey and Future Directions. arXiv 2022 paper bib

    Hao Zhang, Aixin Sun, Wei Jing, Joey Tianyi Zhou

  51. The Elements of End-to-end Deep Face Recognition: A Survey of Recent Advances. ACM Comput. Surv. 2022 paper bib

    Hang Du, Hailin Shi, Dan Zeng, Xiao-Ping Zhang, Tao Mei

  52. The Impact of Machine Learning on 2D/3D Registration for Image-guided Interventions: A Systematic Review and Perspective. Frontiers Robotics AI 2021 paper bib

    Mathias Unberath, Cong Gao, Yicheng Hu, Max Judish, Russell H. Taylor, Mehran Armand, Robert B. Grupp

  53. The Need and Status of Sea Turtle Conservation and Survey of Associated Computer Vision Advances. arXiv 2021 paper bib

    Aditya Jyoti Paul

  54. Transformers in Remote Sensing: A Survey. arXiv 2022 paper bib

    Abdulaziz Amer Aleissaee, Amandeep Kumar, Rao Muhammad Anwer, Salman Khan, Hisham Cholakkal, Gui-Song Xia, Fahad Shahbaz Khan

  55. Transformers Meet Visual Learning Understanding: A Comprehensive Review. arXiv 2022 paper bib

    Yuting Yang, Licheng Jiao, Xu Liu, Fang Liu, Shuyuan Yang, Zhixi Feng, Xu Tang

  56. Video Unsupervised Domain Adaptation with Deep Learning: A Comprehensive Survey. arXiv 2022 paper bib

    Yuecong Xu, Haozhi Cao, Zhenghua Chen, Xiaoli Li, Lihua Xie, Jianfei Yang

  1. A Survey on Contrastive Self-supervised Learning. arXiv 2020 paper bib

    Ashish Jaiswal, Ashwin Ramesh Babu, Mohammad Zaki Zadeh, Debapriya Banerjee, Fillia Makedon

  2. Contrastive Representation Learning: A Framework and Review. IEEE Access 2020 paper bib

    Phuc H. Le-Khac, Graham Healy, Alan F. Smeaton

  3. Self-supervised Learning: Generative or Contrastive. arXiv 2020 paper bib

    Xiao Liu, Fanjin Zhang, Zhenyu Hou, Zhaoyu Wang, Li Mian, Jing Zhang, Jie Tang

  1. A Survey on Curriculum Learning. IEEE Trans. Pattern Anal. Mach. Intell. 2022 paper bib

    Xin Wang, Yudong Chen, Wenwu Zhu

  2. Automatic Curriculum Learning For Deep RL: A Short Survey. IJCAI 2020 paper bib

    Rémy Portelas, Cédric Colas, Lilian Weng, Katja Hofmann, Pierre-Yves Oudeyer

  3. Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey. J. Mach. Learn. Res. 2020 paper bib

    Sanmit Narvekar, Bei Peng, Matteo Leonetti, Jivko Sinapov, Matthew E. Taylor, Peter Stone

  4. Curriculum Learning: A Survey. Int. J. Comput. Vis. 2022 paper bib

    Petru Soviany, Radu Tudor Ionescu, Paolo Rota, Nicu Sebe

  1. A Comprehensive Survey of Dataset Distillation. arXiv 2023 paper bib

    Shiye Lei, Dacheng Tao

  2. A Comprehensive Survey of Image Augmentation Techniques for Deep Learning. arXiv 2022 paper bib

    Mingle Xu, Sook Yoon, Alvaro Fuentes, Dong Sun Park

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  30. Deep Learning for Spatio-Temporal Data Mining: A Survey. IEEE Trans. Knowl. Data Eng. 2022 paper bib

    Senzhang Wang, Jiannong Cao, Philip S. Yu

  31. Deep learning models for predictive maintenance: a survey, comparison, challenges and prospect. arXiv 2020 paper bib

    Oscar Serradilla, Ekhi Zugasti, Urko Zurutuza

  32. Deep Learning-based Spacecraft Relative Navigation Methods: A Survey. arXiv 2021 paper bib

    Jianing Song, Duarte Rondao, Nabil Aouf

  33. Didn't see that coming: a survey on non-verbal social human behavior forecasting. DYAD@ICCV 2021 paper bib

    Germán Barquero, Johnny Núñez, Sergio Escalera, Zhen Xu, Wei-Wei Tu, Isabelle Guyon, Cristina Palmero

  34. DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction. CIKM 2021 paper bib

    Renhe Jiang, Du Yin, Zhaonan Wang, Yizhuo Wang, Jiewen Deng, Hangchen Liu, Zekun Cai, Jinliang Deng, Xuan Song, Ryosuke Shibasaki

  35. Event Prediction in the Big Data Era: A Systematic Survey. ACM Comput. Surv. 2022 paper bib

    Liang Zhao

  36. Fashion Meets Computer Vision: A Survey. ACM Comput. Surv. 2022 paper bib

    Wen-Huang Cheng, Sijie Song, Chieh-Yun Chen, Shintami Chusnul Hidayati, Jiaying Liu

  37. Going Deeper Into Face Detection: A Survey. arXiv 2021 paper bib

    Shervin Minaee, Ping Luo, Zhe Lin, Kevin W. Bowyer

  38. Graph Representation Learning in Biomedicine. arXiv 2021 paper bib

    Michelle M. Li, Kexin Huang, Marinka Zitnik

  39. Graph-based Deep Learning for Communication Networks: A Survey. Comput. Commun. 2022 paper bib

    Weiwei Jiang

  40. How Developers Iterate on Machine Learning Workflows - A Survey of the Applied Machine Learning Literature. arXiv 2018 paper bib

    Doris Xin, Litian Ma, Shuchen Song, Aditya G. Parameswaran

  41. Human Action Recognition from Various Data Modalities: A Review. IEEE Trans. Pattern Anal. Mach. Intell. 2023 paper bib

    Zehua Sun, Qiuhong Ke, Hossein Rahmani, Mohammed Bennamoun, Gang Wang, Jun Liu

  42. Known Operator Learning and Hybrid Machine Learning in Medical Imaging - A Review of the Past, the Present, and the Future. arXiv 2021 paper bib

    Andreas Maier, Harald Köstler, Marco Heisig, Patrick Krauss, Seung Hee Yang

  43. Machine Learning Aided Static Malware Analysis: A Survey and Tutorial. arXiv 2018 paper bib

    Andrii Shalaginov, Sergii Banin, Ali Dehghantanha, Katrin Franke

  44. Machine Learning and Deep Learning -- A review for Ecologists. Methods in Ecology and Evolution 2022 paper bib

    Maximilian Pichler, Florian Hartig

  45. Machine Learning for Cataract Classification and Grading on Ophthalmic Imaging Modalities: A Survey. arXiv 2020 paper bib

    Xiaoqing Zhang, Jiansheng Fang, Yan Hu, Yanwu Xu, Risa Higashita, Jiang Liu

  46. Machine Learning for Electronic Design Automation: A Survey. ACM Trans. Design Autom. Electr. Syst. 2021 paper bib

    Guyue Huang, Jingbo Hu, Yifan He, Jialong Liu, Mingyuan Ma, Zhaoyang Shen, Juejian Wu, Yuanfan Xu, Hengrui Zhang, Kai Zhong, Xuefei Ning, Yuzhe Ma, Haoyu Yang, Bei Yu, Huazhong Yang, Yu Wang

  47. Machine Learning for Survival Analysis: A Survey. ACM Comput. Surv. 2019 paper bib

    Ping Wang, Yan Li, Chandan K. Reddy

  48. Medical Image Segmentation with 3D Convolutional Neural Networks: A Survey. Neurocomputing 2022 paper bib

    S. Niyas, S. J. Pawan, M. Anand Kumar, Jeny Rajan

  49. MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design. arXiv 2022 paper bib

    Yuanqi Du, Tianfan Fu, Jimeng Sun, Shengchao Liu

  50. Multi-modal Sensor Fusion for Auto Driving Perception: A Survey. arXiv 2022 paper bib

    Keli Huang, Botian Shi, Xiang Li, Xin Li, Siyuan Huang, Yikang Li

  51. Physics-Guided Deep Learning for Dynamical Systems: A Survey. arXiv 2021 paper bib

    Rui Wang

  52. Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications. arXiv 2022 paper bib

    Zhongkai Hao, Songming Liu, Yichi Zhang, Chengyang Ying, Yao Feng, Hang Su, Jun Zhu

  53. Predicting the Future from First Person (Egocentric) Vision: A Survey. Comput. Vis. Image Underst. 2021 paper bib

    Ivan Rodin, Antonino Furnari, Dimitrios Mavroeidis, Giovanni Maria Farinella

  54. Prediction of neonatal mortality in Sub-Saharan African countries using data-level linkage of multiple surveys. arXiv 2020 paper bib

    Girmaw Abebe Tadesse, Celia Cintas, Skyler Speakman, Komminist Weldemariam

  55. Requirement Engineering Challenges for AI-intense Systems Development. WAIN@ICSE 2021 paper bib

    Hans-Martin Heyn, Eric Knauss, Amna Pir Muhammad, Olof Eriksson, Jennifer Linder, Padmini Subbiah, Shameer Kumar Pradhan, Sagar Tungal

  56. Short-term Traffic Prediction with Deep Neural Networks: A Survey. IEEE Access 2021 paper bib

    Kyungeun Lee, Moonjung Eo, Euna Jung, Yoonjin Yoon, Wonjong Rhee

  57. Should I Raise The Red Flag? A comprehensive survey of anomaly scoring methods toward mitigating false alarms. arXiv 2019 paper bib

    Zahra Zohrevand, Uwe Glässer

  58. The Threat of Adversarial Attacks on Machine Learning in Network Security - A Survey. arXiv 2019 paper bib

    Olakunle Ibitoye, Rana Abou Khamis, Ashraf Matrawy, M. Omair Shafiq

  59. Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey. IEEE Access 2018 paper bib

    Naveed Akhtar, Ajmal S. Mian

  60. Towards Controllable Protein Design with Conditional Transformers. Nat. Mach. Intell. 2022 paper bib

    Noelia Ferruz, Birte Höcker

  61. Transformers in Remote Sensing: A Survey. arXiv 2022 paper bib

    Abdulaziz Amer Aleissaee, Amandeep Kumar, Rao Muhammad Anwer, Salman Khan, Hisham Cholakkal, Gui-Song Xia, Fahad Shahbaz Khan

  62. Transformers in Time Series: A Survey. arXiv 2022 paper bib

    Qingsong Wen, Tian Zhou, Chaoli Zhang, Weiqi Chen, Ziqing Ma, Junchi Yan, Liang Sun

  63. Understanding racial bias in health using the Medical Expenditure Panel Survey data. arXiv 2019 paper bib

    Moninder Singh, Karthikeyan Natesan Ramamurthy

  64. Urban flows prediction from spatial-temporal data using machine learning: A survey. arXiv 2019 paper bib

    Peng Xie, Tianrui Li, Jia Liu, Shengdong Du, Xin Yang, Junbo Zhang

  65. Using Deep Learning for Visual Decoding and Reconstruction from Brain Activity: A Review. arXiv 2021 paper bib

    Madison Van Horn

  66. Utilising Graph Machine Learning within Drug Discovery and Development. arXiv 2020 paper bib

    Thomas Gaudelet, Ben Day, Arian R. Jamasb, Jyothish Soman, Cristian Regep, Gertrude Liu, Jeremy B. R. Hayter, Richard Vickers, Charles Roberts, Jian Tang, David Roblin, Tom L. Blundell, Michael M. Bronstein, Jake P. Taylor-King

  1. A Survey of Model Compression and Acceleration for Deep Neural Networks. arXiv 2017 paper bib

    Yu Cheng, Duo Wang, Pan Zhou, Tao Zhang

  2. A Survey of Quantization Methods for Efficient Neural Network Inference. arXiv 2021 paper bib

    Amir Gholami, Sehoon Kim, Zhen Dong, Zhewei Yao, Michael W. Mahoney, Kurt Keutzer

  3. A Survey on Deep Neural Network Compression: Challenges, Overview, and Solutions. arXiv 2020 paper bib

    Rahul Mishra, Hari Prabhat Gupta, Tanima Dutta

  4. A Survey on GAN Acceleration Using Memory Compression Technique. arXiv 2021 paper bib

    Dina Tantawy, Mohamed Zahran, Amr Wassal

  5. A Survey on Methods and Theories of Quantized Neural Networks. arXiv 2018 paper bib

    Yunhui Guo

  6. A Survey on Model Compression and Acceleration for Pretrained Language Models. arXiv 2022 paper bib

    Canwen Xu, Julian J. McAuley

  7. An Overview of Neural Network Compression. arXiv 2020 paper bib

    James O'Neill

  8. Compression of Deep Learning Models for Text: A Survey. ACM Trans. Knowl. Discov. Data 2022 paper bib

    Manish Gupta, Puneet Agrawal

  9. Dimensionality Reduced Training by Pruning and Freezing Parts of a Deep Neural Network, a Survey. arXiv 2022 paper bib

    Paul Wimmer, Jens Mehnert, Alexandru Paul Condurache

  10. Efficient Deep Learning: A Survey on Making Deep Learning Models Smaller, Faster, and Better. arXiv 2021 paper bib

    Gaurav Menghani

  11. Pruning Algorithms to Accelerate Convolutional Neural Networks for Edge Applications: A Survey. arXiv 2020 paper bib

    Jiayi Liu, Samarth Tripathi, Unmesh Kurup, Mohak Shah

  12. Pruning and Quantization for Deep Neural Network Acceleration: A Survey. arXiv 2021 paper bib

    Tailin Liang, John Glossner, Lei Wang, Shaobo Shi

  13. Survey of Machine Learning Accelerators. HPEC 2020 paper bib

    Albert Reuther, Peter Michaleas, Michael Jones, Vijay Gadepally, Siddharth Samsi, Jeremy Kepner

  14. Survey on Large Scale Neural Network Training. arXiv 2022 paper bib

    Julia Gusak, Daria Cherniuk, Alena Shilova, Alexandr Katrutsa, Daniel Bershatsky, Xunyi Zhao, Lionel Eyraud-Dubois, Oleg Shlyazhko, Denis Dimitrov, Ivan V. Oseledets, Olivier Beaumont

  1. A Review on Multi-Label Learning Algorithms. IEEE Trans. Knowl. Data Eng. 2014 paper bib

    Min-Ling Zhang, Zhi-Hua Zhou

  2. Multi-Label Classification: An Overview. Int. J. Data Warehous. Min. 2007 paper bib

    Grigorios Tsoumakas, Ioannis Katakis

  3. Multi-label learning: a review of the state of the art and ongoing research. WIREs Data Mining Knowl. Discov. 2014 paper bib

    Eva Lucrecia Gibaja Galindo, Sebastián Ventura

  4. The Emerging Trends of Multi-Label Learning. arXiv 2020 paper bib

    Weiwei Liu, Xiaobo Shen, Haobo Wang, Ivor W. Tsang

  1. A brief review on multi-task learning. Multim. Tools Appl. 2018 paper bib

    Kim-Han Thung, Chong-Yaw Wee

  2. A Survey on Multi-Task Learning. IEEE Trans. Knowl. Data Eng. 2022 paper bib

    Yu Zhang, Qiang Yang

  3. A Survey on Multi-view Learning. arXiv 2013 paper bib

    Chang Xu, Dacheng Tao, Chao Xu

  4. An overview of multi-task learning. National Science Review 2017 paper bib

    Yu Zhang, Qiang Yang

  5. An Overview of Multi-Task Learning in Deep Neural Networks. arXiv 2017 paper bib

    Sebastian Ruder

  6. Multi-Task Learning for Dense Prediction Tasks: A Survey. IEEE Trans. Pattern Anal. Mach. Intell. 2022 paper bib

    Simon Vandenhende, Stamatios Georgoulis, Wouter Van Gansbeke, Marc Proesmans, Dengxin Dai, Luc Van Gool

  7. Multi-task learning for natural language processing in the 2020s: where are we going?. Pattern Recognit. Lett. 2020 paper bib

    Joseph Worsham, Jugal Kalita

  8. Multi-Task Learning with Deep Neural Networks: A Survey. arXiv 2020 paper bib

    Michael Crawshaw

  1. A Survey of Algorithms and Analysis for Adaptive Online Learning. J. Mach. Learn. Res. 2017 paper bib

    H. Brendan McMahan

  2. Online Continual Learning in Image Classification: An Empirical Survey. Neurocomputing 2022 paper bib

    Zheda Mai, Ruiwen Li, Jihwan Jeong, David Quispe, Hyunwoo Kim, Scott Sanner

  3. Online Learning: A Comprehensive Survey. Neurocomputing 2021 paper bib

    Steven C. H. Hoi, Doyen Sahoo, Jing Lu, Peilin Zhao

  4. Preference-based Online Learning with Dueling Bandits: A Survey. J. Mach. Learn. Res. 2021 paper bib

    Viktor Bengs, Róbert Busa-Fekete, Adil El Mesaoudi-Paul, Eyke Hüllermeier

  1. A Survey of Optimization Methods from a Machine Learning Perspective. IEEE Trans. Cybern. 2020 paper bib

    Shiliang Sun, Zehui Cao, Han Zhu, Jing Zhao

  2. A Systematic and Meta-analysis Survey of Whale Optimization Algorithm. Comput. Intell. Neurosci. 2019 paper bib

    Hardi M. Mohammed, Shahla U. Umar, Tarik A. Rashid

  3. An overview of gradient descent optimization algorithms. arXiv 2016 paper bib

    Sebastian Ruder

  4. Convex Optimization Overview. CiteSeerX 2008 paper bib

    Zico Kolter, Honglak Lee

  5. Evolutionary Multitask Optimization: a Methodological Overview, Challenges and Future Research Directions. arXiv 2021 paper bib

    Eneko Osaba, Aritz D. Martinez, Javier Del Ser

  6. Gradient Boosting Machine: A Survey. arXiv 2019 paper bib

    Zhiyuan He, Danchen Lin, Thomas Lau, Mike Wu

  7. Investigating Bi-Level Optimization for Learning and Vision from a Unified Perspective: A Survey and Beyond. IEEE Trans. Pattern Anal. Mach. Intell. 2022 paper bib

    Risheng Liu, Jiaxin Gao, Jin Zhang, Deyu Meng, Zhouchen Lin

  8. Learning Combinatorial Optimization on Graphs: A Survey with Applications to Networking. IEEE Access 2020 paper bib

    Natalia Vesselinova, Rebecca Steinert, Daniel F. Perez-Ramirez, Magnus Boman

  9. Nature-Inspired Optimization Algorithms: Research Direction and Survey. arXiv 2021 paper bib

    Rohit Kumar Sachan, Dharmender Singh Kushwaha

  10. Optimization for deep learning: theory and algorithms. arXiv 2019 paper bib

    Ruoyu Sun

  11. Optimization Problems for Machine Learning: A Survey. Eur. J. Oper. Res. 2021 paper bib

    Claudio Gambella, Bissan Ghaddar, Joe Naoum-Sawaya

  12. Particle Swarm Optimization: A survey of historical and recent developments with hybridization perspectives. Mach. Learn. Knowl. Extr. 2019 paper bib

    Saptarshi Sengupta, Sanchita Basak, Richard A. Peters

  13. Why Do Local Methods Solve Nonconvex Problems?. Beyond the Worst-Case Analysis of Algorithms 2020 paper bib

    Tengyu Ma

  1. A Brief Introduction to Weakly Supervised Learning. National Science Review 2018 paper bib

    Zhi-Hua Zhou

  2. A Survey of Unsupervised Dependency Parsing. COLING 2020 paper bib

    Wenjuan Han, Yong Jiang, Hwee Tou Ng, Kewei Tu

  3. A Survey on Deep Semi-supervised Learning. arXiv 2021 paper bib

    Xiangli Yang, Zixing Song, Irwin King, Zenglin Xu

  4. A survey on Semi-, Self- and Unsupervised Learning for Image Classification. IEEE Access 2021 paper bib

    Lars Schmarje, Monty Santarossa, Simon-Martin Schröder, Reinhard Koch

  5. A Survey on Semi-Supervised Learning Techniques. arXiv 2014 paper bib

    V. Jothi Prakash, L. M. Nithya

  6. Deep Learning for Weakly-Supervised Object Detection and Object Localization: A Survey. arXiv 2021 paper bib

    Feifei Shao, Long Chen, Jian Shao, Wei Ji, Shaoning Xiao, Lu Ye, Yueting Zhuang, Jun Xiao

  7. Graph-based Semi-supervised Learning: A Comprehensive Review. arXiv 2021 paper bib

    Zixing Song, Xiangli Yang, Zenglin Xu, Irwin King

  8. Improvability Through Semi-Supervised Learning: A Survey of Theoretical Results. arXiv 2019 paper bib

    Alexander Mey, Marco Loog

  9. Learning from positive and unlabeled data: a survey. Mach. Learn. 2020 paper bib

    Jessa Bekker, Jesse Davis

  10. Robust Deep Semi-Supervised Learning: A Brief Introduction. arXiv 2022 paper bib

    Lan-Zhe Guo, Zhi Zhou, Yu-Feng Li

  11. Self-Supervised Learning for Recommender Systems: A Survey. arXiv 2022 paper bib

    Junliang Yu, Hongzhi Yin, Xin Xia, Tong Chen, Jundong Li, Zi Huang

  12. Self-Supervised Learning for Videos: A Survey. arXiv 2022 paper bib

    Madeline C. Schiappa, Yogesh S. Rawat, Mubarak Shah

  13. Unsupervised Cross-Lingual Representation Learning. ACL 2019 paper bib

    Sebastian Ruder, Anders Søgaard, Ivan Vulic

  1. A Comprehensive Survey on Transfer Learning. Proc. IEEE 2021 paper bib

    Fuzhen Zhuang, Zhiyuan Qi, Keyu Duan, Dongbo Xi, Yongchun Zhu, Hengshu Zhu, Hui Xiong, Qing He

  2. A Survey of Unsupervised Deep Domain Adaptation. ACM Trans. Intell. Syst. Technol. 2020 paper bib

    Garrett Wilson, Diane J. Cook

  3. A Survey on Deep Transfer Learning. ICANN 2018 paper bib

    Chuanqi Tan, Fuchun Sun, Tao Kong, Wenchang Zhang, Chao Yang, Chunfang Liu

  4. A survey on domain adaptation theory: learning bounds and theoretical guarantees. arXiv 2020 paper bib

    Ievgen Redko, Emilie Morvant, Amaury Habrard, Marc Sebban, Younès Bennani

  5. A Survey on Negative Transfer. IEEE/CAA Journal of Automatica Sinica 2020 paper bib

    Wen Zhang, Lingfei Deng, Lei Zhang, Dongrui Wu

  6. A Survey on Transfer Learning. IEEE Trans. Knowl. Data Eng. 2010 paper bib

    Sinno Jialin Pan, Qiang Yang

  7. A Survey on Transfer Learning in Natural Language Processing. arXiv 2020 paper bib

    Zaid Alyafeai, Maged Saeed AlShaibani, Irfan Ahmad

  8. Evolution of transfer learning in natural language processing. arXiv 2019 paper bib

    Aditya Malte, Pratik Ratadiya

  9. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer. J. Mach. Learn. Res. 2020 paper bib

    Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J. Liu

  10. Neural Unsupervised Domain Adaptation in NLP---A Survey. COLING 2020 paper bib

    Alan Ramponi, Barbara Plank

  11. Source-Free Unsupervised Domain Adaptation: A Survey. arXiv 2023 paper bib

    Yuqi Fang, Pew-Thian Yap, Weili Lin, Hongtu Zhu, Mingxia Liu

  12. Transfer Adaptation Learning: A Decade Survey. arXiv 2019 paper bib

    Lei Zhang

  13. Transfer Learning for Reinforcement Learning Domains: A Survey. J. Mach. Learn. Res. 2009 paper bib

    Matthew E. Taylor, Peter Stone

  14. Transfer Learning in Deep Reinforcement Learning: A Survey. arXiv 2020 paper bib

    Zhuangdi Zhu, Kaixiang Lin, Jiayu Zhou

  15. Transferability in Deep Learning: A Survey. arXiv 2022 paper bib

    Junguang Jiang, Yang Shu, Jianmin Wang, Mingsheng Long

  1. A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability. arXiv 2022 paper bib

    Enyan Dai, Tianxiang Zhao, Huaisheng Zhu, Junjie Xu, Zhimeng Guo, Hui Liu, Jiliang Tang, Suhang Wang

  2. A Survey of Neural Trojan Attacks and Defenses in Deep Learning. arXiv 2022 paper bib

    Jie Wang, Ghulam Mubashar Hassan, Naveed Akhtar

  3. A Survey of Privacy Attacks in Machine Learning. arXiv 2020 paper bib

    Maria Rigaki, Sebastian Garcia

  4. A survey of safety and trustworthiness of deep neural networks: Verification, testing, adversarial attack and defence, and interpretability. Comput. Sci. Rev. 2020 paper bib

    Xiaowei Huang, Daniel Kroening, Wenjie Ruan, James Sharp, Youcheng Sun, Emese Thamo, Min Wu, Xinping Yi

  5. A Survey on Bias and Fairness in Machine Learning. ACM Comput. Surv. 2022 paper bib

    Ninareh Mehrabi, Fred Morstatter, Nripsuta Saxena, Kristina Lerman, Aram Galstyan

  6. Backdoor Learning: A Survey. arXiv 2020 paper bib

    Yiming Li, Baoyuan Wu, Yong Jiang, Zhifeng Li, Shu-Tao Xia

  7. Differential Privacy and Machine Learning: a Survey and Review. arXiv 2014 paper bib

    Zhanglong Ji, Zachary Chase Lipton, Charles Elkan

  8. Fairness in Machine Learning: A Survey. arXiv 2020 paper bib

    Simon Caton, Christian Haas

  9. Local Differential Privacy and Its Applications: A Comprehensive Survey. arXiv 2020 paper bib

    Mengmeng Yang, Lingjuan Lyu, Jun Zhao, Tianqing Zhu, Kwok-Yan Lam

  10. Privacy in Deep Learning: A Survey. arXiv 2020 paper bib

    Fatemehsadat Mireshghallah, Mohammadkazem Taram, Praneeth Vepakomma, Abhishek Singh, Ramesh Raskar, Hadi Esmaeilzadeh

  11. Taxonomy of Machine Learning Safety: A Survey and Primer. ACM Comput. Surv. 2023 paper bib

    Sina Mohseni, Haotao Wang, Chaowei Xiao, Zhiding Yu, Zhangyang Wang, Jay Yadawa

  12. Technology Readiness Levels for Machine Learning Systems. arXiv 2021 paper bib

    Alexander Lavin, Ciarán M. Gilligan-Lee, Alessya Visnjic, Siddha Ganju, Dava Newman, Sujoy Ganguly, Danny Lange, Atilim Günes Baydin, Amit Sharma, Adam Gibson, Yarin Gal, Eric P. Xing, Chris Mattmann, James Parr

  13. The Creation and Detection of Deepfakes: A Survey. ACM Comput. Surv. 2022 paper bib

    Yisroel Mirsky, Wenke Lee

  14. Toward Transparent AI: A Survey on Interpreting the Inner Structures of Deep Neural Networks. arXiv 2022 paper bib

    Tilman Räuker, Anson Ho, Stephen Casper, Dylan Hadfield-Menell

  15. Trustworthy AI: From Principles to Practices. ACM Comput. Surv. 2023 paper bib

    Bo Li, Peng Qi, Bo Liu, Shuai Di, Jingen Liu, Jiquan Pei, Jinfeng Yi, Bowen Zhou

  16. Trustworthy Graph Neural Networks: Aspects, Methods and Trends. arXiv 2022 paper bib

    He Zhang, Bang Wu, Xingliang Yuan, Shirui Pan, Hanghang Tong, Jian Pei

  17. Tutorial: Safe and Reliable Machine Learning. arXiv 2019 paper bib

    Suchi Saria, Adarsh Subbaswamy

  18. When Machine Learning Meets Privacy: A Survey and Outlook. ACM Comput. Surv. 2022 paper bib

    Bo Liu, Ming Ding, Sina Shaham, Wenny Rahayu, Farhad Farokhi, Zihuai Lin

  19. Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning. arXiv 2022 paper bib

    Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis, Sebastiano Vascon, Werner Zellinger, Bernhard Alois Moser, Alina Oprea, Battista Biggio, Marcello Pelillo, Fabio Roli

Team Members

The project is maintained by

Natural Language Processing Lab., School of Computer Science and Engineering, Northeastern University

NiuTrans Research

Please feel free to contact us if you have any questions (libei_neu [at] outlook.com).

Acknowledge

We would like to thank the people who have contributed to this project. They are

Chuanhao Lv, Kaiyan Chang, Ziyang Wang, Shuhan Zhou, Nuo Xu, Bei Li, Yinqiao Li, Quan Du, Xin Zeng, Laohu Wang, Chenglong Wang, Xiaoqian Liu, Xuanjun Zhou, Jingnan Zhang, Yongyu Mu, Zefan Zhou, Yanhong Jiang, Xinyang Zhu, Xingyu Liu, Dong Bi, Ping Xu, Zijian Li, Fengning Tian, Hui Liu, Kai Feng, Yuhao Zhang, Chi Hu, Di Yang, Lei Zheng, Hexuan Chen, Zeyang Wang, Tengbo Liu, Xia Meng, Weiqiao Shan, Tao Zhou, Runzhe Cao, Yingfeng Luo, Binghao Wei, Wandi Xu, Yan Zhang, Yichao Wang, Mengyu Ma, Zihao Liu

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A collection of 1000+ survey papers on Natural Language Processing (NLP) and Machine Learning (ML).

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