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Despite agreement on the importance of detecting out-of-distribution (OOD) examples, there is little consensus on the formal definition of OOD examples and how to best detect them.
RoBERTa: A robustly optimized BERT pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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Scaling out-of-distribution detection for real-world settings
Dan Hendrycks, Steven Basart, Mantas Mazeika, Mohammadreza Mostajabi, Jacob Steinhardt, and Dawn Song. 2020a · 1911
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Alireza Borjali, Martin Magneli, David Shin, Henrik Malchau, Orhun K. Muratoglu, and Kartik M. Varadarajan. 2020 · 2004
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Robust out-of-distribution detection via informative outlier mining
Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang, and Somesh Jha. 2020 · 2006
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Misinformation has high perplexity
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Hao Liu and Pieter Abbeel. 2020 · 2007
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Contrastive training for improved out-of-distribution detection
Jim Winkens, Rudy Bunel, Abhijit Guha Roy, Robert Stanforth, Vivek Natarajan, Joseph R. Ledsam, Patricia MacWilliams, Pushmeet Kohli, Alan Karthikesalingam, Simon Kohl, A. Taylan Cemgil, S. M. Ali Eslami, and Olaf Ronneberger. 2020 · 2007
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Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. 2011 · 2011
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WILDS: A benchmark of in-the-wild distribution shifts
Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Sara Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, and Percy Liang. 2020a · 2012
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WILDS: A benchmark of in-the-wild distribution shifts
Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Sara Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, and Percy Liang. 2020b · 2012
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Toward open set recognition
Walter J. Scheirer, Anderson de Rezende Rocha, Archana Sapkota, and Terrance E. Boult. 2013 · 2013
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Recursive deep models for semantic compositionality over a sentiment treebank
Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D. Manning, Andrew Y. Ng, and Christopher Potts. 2013 · 2013
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A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015 · 2015
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Dbpedia–a large-scale, multilingual knowledge base extracted from wikipedia
Jens Lehmann, Robert Isele, Max Jakob, Anja Jentzsch, Dimitris Kontokostas, Pablo N Mendes, Sebastian Hellmann, Mohamed Morsey, Patrick Van Kleef, Sören Auer, et al. 2015 · 2015
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Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015 · 2015
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Concrete problems in AI safety
Dario Amodei, Chris Olah, Jacob Steinhardt, Paul F. Christiano, John Schulman, and Dan Mané. 2016 · 2016
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An empirical analysis of formality in online communication
Ellie Pavlick and Joel R. Tetreault. 2016 · 2016
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Adversarial examples are not easily detected: Bypassing ten detection methods
Nicholas Carlini and David A. Wagner. 2017 · 2017
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A baseline for detecting misclassified and out-of-distribution examples in neural networks
Dan Hendrycks and Kevin Gimpel. 2017 · 2017
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Pointer sentinel mixture models
Stephen Merity, Caiming Xiong, James Bradbury, and Richard Socher. 2017 · 2017
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A survey of domain adaptation for neural machine translation
Chenhui Chu and Rui Wang. 2018 · 2018
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Style transfer in text: Exploration and evaluation
Zhenxin Fu, Xiaoye Tan, Nanyun Peng, Dongyan Zhao, and Rui Yan. 2018 · 2018
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A simple unified framework for detecting out-of-distribution samples and adversarial attacks
Kimin Lee, Kibok Lee, Honglak Lee, and Jinwoo Shin. 2018 · 2018
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Enhancing the reliability of out-of-distribution image detection in neural networks
Shiyu Liang, Yixuan Li, and R. Srikant. 2018 · 2018
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News category dataset
Rishabh Misra. 2018 · 2018
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Detecting semantic anomalies
Faruk Ahmed and Aaron C. Courville. 2020 · 2020
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Calibration of pre-trained transformers
Shrey Desai and Greg Durrett. 2020 · 2020
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Evaluating factuality in generation with dependency-level entailment
Tanya Goyal and Greg Durrett. 2020 · 2020
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Pretrained transformers improve out-of-distribution robustness
Dan Hendrycks, Xiaoyuan Liu, Eric Wallace, Adam Dziedzic, Rishabh Krishnan, and Dawn Song. 2020b · 2020
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The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2020 · 2020
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Generalized ODIN: detecting out-of-distribution image without learning from out-of-distribution data
Yen-Chang Hsu, Yilin Shen, Hongxia Jin, and Zsolt Kira. 2020 · 2020
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Know what you don’t know: Unanswerable questions for SQuAD
P. Rajpurkar, R. Jia, and P. Liang. 2018 · 2018
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Out-of-domain detection based on generative adversarial network
Seonghan Ryu, Sangjun Koo, Hwanjo Yu, and Gary Geunbae Lee. 2018 · 2018
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GLUE: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman. 2018b · 2018
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A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel Bowman. 2018 · 2018
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Nuanced metrics for measuring unintended bias with real data for text classification
Daniel Borkan, Lucas Dixon, Jeffrey Sorensen, Nithum Thain, and Lucy Vasserman. 2019a · 2019
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Divyansh Kaushik, Eduard H. Hovy, and Zachary Chase Lipton. 2020 · 2020
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Why normalizing flows fail to detect out-of-distribution data
Polina Kirichenko, Pavel Izmailov, and Andrew Gordon Wilson. 2020 · 2020
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Calibrated language model fine-tuning for in- and out-of-distribution data
Lingkai Kong, Haoming Jiang, Yuchen Zhuang, Jie Lyu, Tuo Zhao, and Chao Zhang. 2020 · 2020
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Beyond accuracy: Behavioral testing of NLP models with checklist
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Distributionally robust neural networks
Shiori Sagawa, Pang Wei Koh, Tatsunori B. Hashimoto, and Percy Liang. 2020 · 2020
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Test-time training with self-supervision for generalization under distribution shifts
Yu Sun, Xiaolong Wang, Zhuang Liu, John Miller, Alexei A. Efros, and Moritz Hardt. 2020 · 2020
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Hybrid models for open set recognition
Hongjie Zhang, Ang Li, Jie Guo, and Yanwen Guo. 2020a · 2020
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Hybrid models for open set recognition
Hongjie Zhang, Ang Li, Jie Guo, and Yanwen Guo. 2020b · 2020
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Out-of-domain detection for natural language understanding in dialog systems
Yinhe Zheng, Guanyi Chen, and Minlie Huang. 2020 · 2020
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Domain divergences: A survey and empirical analysis
Abhinav Ramesh Kashyap, Devamanyu Hazarika, Min-Yen Kan, and Roger Zimmermann. 2021 · 2021
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The art of abstention: Selective prediction and error regularization for natural language processing
Ji Xin, Raphael Tang, Yaoliang Yu, and Jimmy Lin. 2021 · 2021
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Contrastive out-of-distribution detection for pretrained transformers
Wenxuan Zhou and Muhao Chen. 2021 · 2021
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