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Out-of-distribution (OOD) detection aims at identifying samples from unknown classes, playing a crucial role in trustworthy models against errors on unexpected inputs.
Statistics for experimenters: an introduction to design, data analysis, and model building
Ravi Parameswaran · 1979
Earlier work this paper cites.
WordNet: An Electronic Lexical Database
Christiane Fellbaum · 1998
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The case against accuracy estimation for comparing induction algorithms
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A tutorial on energy-based learning
Yann LeCun, Sumit Chopra, Raia Hadsell, M Ranzato, and F Huang · 2006
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Learning multiple layers of features from tiny images
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Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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A baseline for detecting misclassified and out-of-distribution examples in neural networks
Dan Hendrycks and Kevin Gimpel · 2017
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Learning confidence for out-of-distribution detection in neural networks
Terrance DeVries and Graham W Taylor · 2018
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The inaturalist species classification and detection dataset
Grant Van Horn, Oisin Mac Aodha, Yang Song, Yin Cui, Chen Sun, Alexander Shepard, Hartwig Adam, Pietro Perona, and Serge J. Belongie · 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
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Enhancing the reliability of out-of-distribution image detection in neural networks
Shiyu Liang, Yixuan Li, and R. Srikant · 2018
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Places: A 10 million image database for scene recognition
Bolei Zhou, Àgata Lapedriza, Aditya Khosla, Aude Oliva, and Antonio Torralba · 2018
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Ziwei Liu, Zhongqi Miao, Xiaohang Zhan, Jiayun Wang, Boqing Gong, and Stella X. Yu · 2019
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Do imagenet classifiers generalize to imagenet?
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Learning robust global representations by penalizing local predictive power
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Zhongzhi Chen, Guang Liu, Bo-Wen Zhang, Fulong Ye, Qinghong Yang, and Ledell Wu · 2022
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Unknown-aware object detection: Learning what you don’t know from videos in the wild
Xuefeng Du, Xin Wang, Gabriel Gozum, and Yixuan Li · 2022
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Zero-shot out-of-distribution detection based on the pre-trained model clip
Sepideh Esmaeilpour, Bing Liu, Eric Robertson, and Lei Shu · 2022
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Dice: Leveraging sparsification for out-of-distribution detection
Yiyou Sun and Yixuan Li · 2022
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Out-of-distribution detection with deep nearest neighbors
Yiyou Sun, Yifei Ming, Xiaojin Zhu, and Yixuan Li · 2022
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Open-set recognition: A good closed-set classifier is all you need
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Haohan Wang, Songwei Ge, Zachary C. Lipton, and Eric P. Xing · 2019
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Certifiably adversarially robust detection of out-of-distribution data
Julian Bitterwolf, Alexander Meinke, and Matthias Hein · 2020
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Energy-based out-of-distribution detection
Weitang Liu, Xiaoyun Wang, John D. Owens, and Yixuan Li · 2020
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Csi: Novelty detection via contrastive learning on distributionally shifted instances
Jihoon Tack, Sangwoo Mo, Jongheon Jeong, and Jinwoo Shin · 2020
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Exploring the limits of out-of-distribution detection
Stanislav Fort, Jie Ren, and Balaji Lakshminarayanan · 2021
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On the importance of gradients for detecting distributional shifts in the wild
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Scaling up visual and vision-language representation learning with noisy text supervision
Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc Le, Yun-Hsuan Sung, Zhen Li, and Tom Duerig · 2021
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Sagar Vaze, Kai Han, Andrea Vedaldi, and Andrew Zisserman · 2022
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Vim: Out-of-distribution with virtual-logit matching
Haoqi Wang, Zhizhong Li, Litong Feng, and Wayne Zhang · 2022
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Mitigating neural network overconfidence with logit normalization
Hongxin Wei, Renchunzi Xie, Hao Cheng, Lei Feng, Bo An, and Yixuan Li · 2022
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Groupvit: Semantic segmentation emerges from text supervision
Jiarui Xu, Shalini De Mello, Sifei Liu, Wonmin Byeon, Thomas Breuel, Jan Kautz, and Xiaolong Wang · 2022
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Extremely simple activation shaping for out-of-distribution detection
Andrija Djurisic, Nebojsa Bozanic, Arjun Ashok, and Rosanne Liu · 2023
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Detecting out-of-distribution data through in-distribution class prior
Xue Jiang, Feng Liu, Zhen Fang, Hong Chen, Tongliang Liu, Feng Zheng, and Bo Han · 2023
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Visual instruction tuning
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2023
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Cider: Exploiting hyperspherical embeddings for out-of-distribution detection
Yifei Ming, Yiyou Sun, Ousmane Dia, and Yixuan Li · 2023
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Non-parametric outlier synthesis
Leitian Tao, Xuefeng Du, Xiaojin Zhu, and Yixuan Li · 2023
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Clipn for zero-shot ood detection: Teaching clip to say no
Hualiang Wang, Yi Li, Huifeng Yao, and Xiaomeng Li · 2023
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