What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments?

10 June 2021

Liang Zheng

Papers citing "What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments?"

50 / 52 papers shown

Title
Unveiling AI's Blind Spots: An Oracle for In-Domain, Out-of-Domain, and Adversarial Errors Shuangpeng Han Mengmi Zhang 111 0 0 03 Oct 2024
Poor-Supervised Evaluation for SuperLLM via Mutual Consistency Peiwen Yuan Shaoxiong Feng Yiwei Li Xinglin Wang Boyuan Pan Heda Wang Yao Hu Kan Li 28 1 0 25 Aug 2024
Source-Free Domain-Invariant Performance Prediction Ekaterina Khramtsova Mahsa Baktashmotlagh Guido Zuccon Xi Wang Mathieu Salzmann UQCV 40 1 0 05 Aug 2024
Assessing Model Generalization in Vicinity Yuchi Liu Yifan Sun Jingdong Wang Liang Zheng AAML 28 0 0 13 Jun 2024
A Framework for Efficient Model Evaluation through Stratification, Sampling, and Estimation Riccardo Fogliato Pratik Patil Mathew Monfort Pietro Perona 22 1 0 11 Jun 2024
MANO: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts Renchunzi Xie Ambroise Odonnat Vasilii Feofanov Weijian Deng Jianfeng Zhang Bo An 37 2 0 29 May 2024
Self-supervised visual learning in the low-data regime: a comparative evaluation Sotirios Konstantakos Despina Ioanna Chalkiadaki Ioannis Mademlis Yuki M. Asano E. Gavves Georgios Th. Papadopoulos 29 6 0 26 Apr 2024
Temporal Generalization Estimation in Evolving Graphs Bin Lu Tingyan Ma Xiaoying Gan Xinbing Wang Yunqiang Zhu Cheng Zhou Shiyu Liang 27 1 0 07 Apr 2024
Predicting the Performance of Foundation Models via Agreement-on-the-Line Aman Mehra Rahul Saxena Taeyoun Kim Christina Baek Zico Kolter Aditi Raghunathan UQCV 41 1 0 02 Apr 2024
Bounding Box Stability against Feature Dropout Reflects Detector Generalization across Environments Yang Yang Wenhai Wang Zhe Chen Jifeng Dai Liang Zheng 41 2 0 20 Mar 2024
Online GNN Evaluation Under Test-time Graph Distribution Shifts Xin-Yang Zheng Dongjin Song Qingsong Wen Bo Du Shirui Pan 34 6 0 15 Mar 2024
A Survey on Evaluation of Out-of-Distribution Generalization Han Yu Jiashuo Liu Xingxuan Zhang Jiayun Wu Peng Cui OOD 42 9 0 04 Mar 2024
Domain-adaptive and Subgroup-specific Cascaded Temperature Regression for Out-of-distribution Calibration Jiexin Wang Jiahao Chen Bing-Huang Su UQCV 17 0 0 14 Feb 2024
Leveraging Gradients for Unsupervised Accuracy Estimation under Distribution Shift Renchunzi Xie Ambroise Odonnat Vasilii Feofanov I. Redko Jianfeng Zhang Bo An UQCV 70 1 0 17 Jan 2024
GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels Xin-Yang Zheng Miao Zhang C. Chen Soheila Molaei Chuan Zhou Shirui Pan GNN 29 14 0 23 Oct 2023
On the Transferability of Learning Models for Semantic Segmentation for Remote Sensing Data Rongjun Qin Guixiang Zhang Yang Tang 25 1 0 16 Oct 2023
Heterogeneous Generative Knowledge Distillation with Masked Image Modeling Ziming Wang Shumin Han Xiaodi Wang Jing Hao Xianbin Cao Baochang Zhang VLM 27 0 0 18 Sep 2023
Selecting which Dense Retriever to use for Zero-Shot Search Ekaterina Khramtsova Shengyao Zhuang Mahsa Baktashmotlagh Xi Wang Guido Zuccon 27 6 0 18 Sep 2023
CAME: Contrastive Automated Model Evaluation Ru Peng Qiuyang Duan Haobo Wang Jiachen Ma Yanbo Jiang Yongjun Tu Xiu Jiang J. Zhao ELM 23 4 0 22 Aug 2023
Test-Time Poisoning Attacks Against Test-Time Adaptation Models Tianshuo Cong Xinlei He Yun Shen Yang Zhang AAML TTA 19 5 0 16 Aug 2023
Distance Matters For Improving Performance Estimation Under Covariate Shift Mélanie Roschewitz Ben Glocker 23 1 0 14 Aug 2023
Unsupervised Accuracy Estimation of Deep Visual Models using Domain-Adaptive Adversarial Perturbation without Source Samples JoonHo Lee J. Woo H. Moon Kwonho Lee 14 2 0 19 Jul 2023
ProbVLM: Probabilistic Adapter for Frozen Vision-Language Models Uddeshya Upadhyay Shyamgopal Karthik Massimiliano Mancini Zeynep Akata MLLM VLM 16 3 0 01 Jul 2023
On Orderings of Probability Vectors and Unsupervised Performance Estimation Muhammad Maaz Rui Qiao Yiheng Zhou Renxian Zhang 11 0 0 16 Jun 2023
(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy Elan Rosenfeld Saurabh Garg UQCV 22 4 0 01 Jun 2023
Characterizing Out-of-Distribution Error via Optimal Transport Yuzhe Lu Yilong Qin Runtian Zhai Andrew Shen Ketong Chen Zhenlin Wang Soheil Kolouri Simon Stepputtis Joseph Campbell Katia P. Sycara OODD 27 10 0 25 May 2023
Toward Auto-evaluation with Confidence-based Category Relation-aware Regression Jiexin Wang Jiahao Chen Bing-Huang Su 10 1 0 17 Apr 2023
K-means Clustering Based Feature Consistency Alignment for Label-free Model Evaluation Shuyu Miao Lin Zheng J. Liu and Hong Jin 23 5 0 17 Apr 2023
On the Importance of Feature Separability in Predicting Out-Of-Distribution Error Renchunzi Xie Hongxin Wei Lei Feng Yuzhou Cao Bo An OODD OOD 22 10 0 27 Mar 2023
On the Efficacy of Generalization Error Prediction Scoring Functions Puja Trivedi Danai Koutra Jayaraman J. Thiagarajan 11 0 0 23 Mar 2023
A Bag-of-Prototypes Representation for Dataset-Level Applications Wei-Chih Tu Weijian Deng Tom Gedeon Liang Zheng 38 9 0 23 Mar 2023
Unsupervised Evaluation of Out-of-distribution Detection: A Data-centric Perspective Yuhang Zhang Weihong Deng Liang Zheng OODD 24 4 0 16 Feb 2023
Trust, but Verify: Using Self-Supervised Probing to Improve Trustworthiness Ailin Deng Shen Li Miao Xiong Zhirui Chen Bryan Hooi 16 4 0 06 Feb 2023
Confidence and Dispersity Speak: Characterising Prediction Matrix for Unsupervised Accuracy Estimation Weijian Deng Yumin Suh Stephen Gould Liang Zheng UQCV 21 12 0 02 Feb 2023
What Images are More Memorable to Machines? Junlin Han Huangying Zhan Jie Hong Pengfei Fang Hongdong Li L. Petersson Ian Reid 20 3 0 14 Nov 2022
Composite Learning for Robust and Effective Dense Predictions Menelaos Kanakis Thomas E. Huang David Brüggemann F. I. F. Richard Yu Luc Van Gool SSL 34 3 0 13 Oct 2022
Test-time Recalibration of Conformal Predictors Under Distribution Shift Based on Unlabeled Examples Fatih Yilmaz Reinhard Heckel 13 0 0 09 Oct 2022
HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions Lingjiao Chen Zhihua Jin Sabri Eyuboglu Christopher Ré Matei A. Zaharia James Y. Zou 40 9 0 18 Sep 2022
Estimating and Explaining Model Performance When Both Covariates and Labels Shift Lingjiao Chen Matei A. Zaharia James Y. Zou 20 15 0 18 Sep 2022
Improving Self-supervised Learning for Out-of-distribution Task via Auxiliary Classifier Harshita Boonlia T. Dam Md Meftahul Ferdaus S. Anavatti Ankan Mullick OODD 14 4 0 07 Sep 2022
On the Strong Correlation Between Model Invariance and Generalization Weijian Deng Stephen Gould Liang Zheng OOD 26 16 0 14 Jul 2022
Predicting is not Understanding: Recognizing and Addressing Underspecification in Machine Learning Damien Teney Maxime Peyrard Ehsan Abbasnejad 25 29 0 06 Jul 2022
Predicting Out-of-Domain Generalization with Neighborhood Invariance Nathan Ng Neha Hulkund Kyunghyun Cho Marzyeh Ghassemi OOD 11 4 0 05 Jul 2022
Agreement-on-the-Line: Predicting the Performance of Neural Networks under Distribution Shift Christina Baek Yiding Jiang Aditi Raghunathan Zico Kolter 24 79 0 27 Jun 2022
Performance Prediction Under Dataset Shift Simona Maggio Victor Bouvier L. Dreyfus-Schmidt OOD AI4TS 16 2 0 21 Jun 2022
Attribute Descent: Simulating Object-Centric Datasets on the Content Level and Beyond Yue Yao Liang Zheng Xiaodong Yang Milind Napthade Tom Gedeon 24 17 0 28 Feb 2022
Predicting Out-of-Distribution Error with the Projection Norm Yaodong Yu Zitong Yang Alexander Wei Yi-An Ma Jacob Steinhardt OODD 7 43 0 11 Feb 2022
Leveraging Unlabeled Data to Predict Out-of-Distribution Performance Saurabh Garg Sivaraman Balakrishnan Zachary Chase Lipton Behnam Neyshabur Hanie Sedghi OODD OOD 32 124 0 11 Jan 2022
Label-Free Model Evaluation with Semi-Structured Dataset Representations Xiaoxiao Sun Yunzhong Hou Hongdong Li Liang Zheng 13 11 0 01 Dec 2021
Ranking Models in Unlabeled New Environments Xiaoxiao Sun Yunzhong Hou Weijian Deng Hongdong Li Liang Zheng OOD 13 9 0 23 Aug 2021