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A Baseline for Detecting Misclassified and Out-of-Distribution Examples
  in Neural Networks

A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

7 October 2016
Dan Hendrycks
Kevin Gimpel
    UQCV
ArXivPDFHTML

Papers citing "A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks"

50 / 770 papers shown
Title
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LoD: Loss-difference OOD Detection by Intentionally Label-Noisifying Unlabeled Wild Data
LoD: Loss-difference OOD Detection by Intentionally Label-Noisifying Unlabeled Wild Data
Chuanxing Geng
Qifei Li
Xinrui Wang
Dong Liang
Songcan Chen
Pong C. Yuen
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HybridServe: Efficient Serving of Large AI Models with Confidence-Based Cascade Routing
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Leyang Xue
Yao Fu
Luo Mai
Mahesh K. Marina
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Unsupervised Detection of Distribution Shift in Inverse Problems using Diffusion Models
Unsupervised Detection of Distribution Shift in Inverse Problems using Diffusion Models
Shirin Shoushtari
Edward P. Chandler
M. Salman Asif
Ulugbek S. Kamilov
DiffM
30
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0
16 May 2025
On the Learning with Augmented Class via Forests
On the Learning with Augmented Class via Forests
Fan Xu
Wuyang Chen
Wei Gao
34
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Performance Estimation in Binary Classification Using Calibrated Confidence
Performance Estimation in Binary Classification Using Calibrated Confidence
Juhani Kivimäki
Jakub Białek
W. Kuberski
J. Nurminen
55
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0
08 May 2025
Graph Synthetic Out-of-Distribution Exposure with Large Language Models
Graph Synthetic Out-of-Distribution Exposure with Large Language Models
Haoyan Xu
Zhengtao Yao
Ziyi Wang
Zhan Cheng
Xiyang Hu
Mengyuan Li
Yue Zhao
OODD
55
1
0
29 Apr 2025
Open-set Anomaly Segmentation in Complex Scenarios
Open-set Anomaly Segmentation in Complex Scenarios
Song Xia
Yi Yu
Henghui Ding
Wenhan Yang
Shixuan Liu
Alex C. Kot
Xudong Jiang
DiffM
57
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0
28 Apr 2025
Comparing Uncertainty Measurement and Mitigation Methods for Large Language Models: A Systematic Review
Comparing Uncertainty Measurement and Mitigation Methods for Large Language Models: A Systematic Review
Toghrul Abbasli
Kentaroh Toyoda
Yuan Wang
Leon Witt
Muhammad Asif Ali
Yukai Miao
Dan Li
Qingsong Wei
UQCV
94
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0
25 Apr 2025
Dream-Box: Object-wise Outlier Generation for Out-of-Distribution Detection
Dream-Box: Object-wise Outlier Generation for Out-of-Distribution Detection
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T. Breckon
OODD
249
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Enhancing System Self-Awareness and Trust of AI: A Case Study in Trajectory Prediction and Planning
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Zurab Mujirishvili
Knut Graichen
63
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Avoiding Leakage Poisoning: Concept Interventions Under Distribution Shifts
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Gabriele Dominici
Pietro Barbiero
Z. Shams
M. Jamnik
KELM
269
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24 Apr 2025
Bounded and Uniform Energy-based Out-of-distribution Detection for Graphs
Bounded and Uniform Energy-based Out-of-distribution Detection for Graphs
Shenzhi Yang
Bin Liang
An Liu
Lin Gui
Xingkai Yao
Xiaofang Zhang
OODD
80
4
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18 Apr 2025
Monitor and Recover: A Paradigm for Future Research on Distribution Shift in Learning-Enabled Cyber-Physical Systems
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Vivian Lin
Insup Lee
37
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The Others: Naturally Isolating Out-of-Distribution Samples for Robust Open-Set Semi-Supervised Learning
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You Rim Choi
Subeom Park
Seojun Heo
Eunchung Noh
Hyung-Sin Kim
OODD
54
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0
17 Apr 2025
Are We Done with Object-Centric Learning?
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Alexander Rubinstein
Ameya Prabhu
Matthias Bethge
Seong Joon Oh
OCL
742
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JailDAM: Jailbreak Detection with Adaptive Memory for Vision-Language Model
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Yi Nian
Shenzhe Zhu
Yuehan Qin
Li Li
Ziyi Wang
Chaowei Xiao
Yue Zhao
35
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0
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ProtoGCD: Unified and Unbiased Prototype Learning for Generalized Category Discovery
ProtoGCD: Unified and Unbiased Prototype Learning for Generalized Category Discovery
Shijie Ma
Fei Zhu
Xu-Yao Zhang
Cheng-Lin Liu
45
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VisTa: Visual-contextual and Text-augmented Zero-shot Object-level OOD Detection
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Bin Zhang
Xiaoyang Qu
Guokuan Li
Jiguang Wan
Jianzong Wang
VLM
59
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BackMix: Regularizing Open Set Recognition by Removing Underlying Fore-Background Priors
BackMix: Regularizing Open Set Recognition by Removing Underlying Fore-Background Priors
Yu Wang
Junxian Mu
Hongzhi Huang
Qilong Wang
Pengfei Zhu
Q. Hu
60
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H2ST: Hierarchical Two-Sample Tests for Continual Out-of-Distribution Detection
H2ST: Hierarchical Two-Sample Tests for Continual Out-of-Distribution Detection
Yuhang Liu
Wenjie Zhao
Yunhui Guo
OODD
79
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19 Mar 2025
Structural Entropy Guided Unsupervised Graph Out-Of-Distribution Detection
Yue Hou
He Zhu
Ruomei Liu
Yingke Su
Jinxiang Xia
Junran Wu
Ke Xu
OODD
116
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Probing Network Decisions: Capturing Uncertainties and Unveiling Vulnerabilities Without Label Information
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SphOR: A Representation Learning Perspective on Open-set Recognition for Identifying Unknown Classes in Deep Learning Models
SphOR: A Representation Learning Perspective on Open-set Recognition for Identifying Unknown Classes in Deep Learning Models
Nadarasar Bahavan
Sachith Seneviratne
Saman K. Halgamuge
BDL
50
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OT-DETECTOR: Delving into Optimal Transport for Zero-shot Out-of-Distribution Detection
OT-DETECTOR: Delving into Optimal Transport for Zero-shot Out-of-Distribution Detection
Yu Liu
Hao Tang
Haiqi Zhang
Jing Qin
Zechao Li
OODD
69
0
0
09 Mar 2025
Secure On-Device Video OOD Detection Without Backpropagation
Secure On-Device Video OOD Detection Without Backpropagation
Li Li
Peilin Cai
Yuxiao Zhou
Zhiyu Ni
Renjie Liang
You Qin
Yi Nian
Zhuowen Tu
Xiyang Hu
Yue Zhao
OODD
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71
2
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08 Mar 2025
Out-of-Distribution Segmentation in Autonomous Driving: Problems and State of the Art
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Youssef Shoeb
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Hanno Gottschalk
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90
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CADRef: Robust Out-of-Distribution Detection via Class-Aware Decoupled Relative Feature Leveraging
Zhiwei Ling
Yachen Chang
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Xinkui Zhao
Kingsum Chow
Shuiguang Deng
OODD
70
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01 Mar 2025
HALO: Robust Out-of-Distribution Detection via Joint Optimisation
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Hugo Lyons Keenan
S. Erfani
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214
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Shh, don't say that! Domain Certification in LLMs
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66
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FilterRAG: Zero-Shot Informed Retrieval-Augmented Generation to Mitigate Hallucinations in VQA
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S M Sarwar
82
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Decoupled Graph Energy-based Model for Node Out-of-Distribution Detection on Heterophilic Graphs
Decoupled Graph Energy-based Model for Node Out-of-Distribution Detection on Heterophilic Graphs
Yuhan Chen
Yihong Luo
Yifan Song
Pengwen Dai
Jing Tang
Xiaochun Cao
OODD
53
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A graph neural network-based model with Out-of-Distribution Robustness for enhancing Antiretroviral Therapy Outcome Prediction for HIV-1
A graph neural network-based model with Out-of-Distribution Robustness for enhancing Antiretroviral Therapy Outcome Prediction for HIV-1
Giulia Di Teodoro
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Anders Sönnerborg
Maurizio Zazzi
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77
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Logit Disagreement: OoD Detection with Bayesian Neural Networks
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Large Language Models for Anomaly and Out-of-Distribution Detection: A Survey
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GOLD: Graph Out-of-Distribution Detection via Implicit Adversarial Latent Generation
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Out-of-Distribution Detection using Synthetic Data Generation
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