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Classification Confidence Estimation with Test-Time Data-Augmentation

Classification Confidence Estimation with Test-Time Data-Augmentation

30 June 2020
Yuval Bahat
Gregory Shakhnarovich
ArXiv (abs)PDFHTML

Papers citing "Classification Confidence Estimation with Test-Time Data-Augmentation"

11 / 11 papers shown
Title
FESTA: Functionally Equivalent Sampling for Trust Assessment of Multimodal LLMs
FESTA: Functionally Equivalent Sampling for Trust Assessment of Multimodal LLMsConference on Empirical Methods in Natural Language Processing (EMNLP), 2025
Debarpan Bhattacharya
Apoorva Kulkarni
Sriram Ganapathy
60
0
0
20 Sep 2025
Benchmarking and Confidence Evaluation of LALMs For Temporal Reasoning
Benchmarking and Confidence Evaluation of LALMs For Temporal Reasoning
Debarpan Bhattacharya
Apoorva Kulkarni
Sriram Ganapathy
234
1
0
19 May 2025
A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions
A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future DirectionsACM Computing Surveys (ACM CSUR), 2024
Ola Shorinwa
Zhiting Mei
Justin Lidard
Allen Z. Ren
Anirudha Majumdar
HILMLRM
255
50
0
07 Dec 2024
Deep Nets with Subsampling Layers Unwittingly Discard Useful Activations
  at Test-Time
Deep Nets with Subsampling Layers Unwittingly Discard Useful Activations at Test-TimeEuropean Conference on Computer Vision (ECCV), 2024
Chiao-An Yang
Ziwei Liu
Raymond A. Yeh
112
1
0
01 Oct 2024
Catchém all: Classification of Rare, Prominent, and Novel Malware
  Families
Catchém all: Classification of Rare, Prominent, and Novel Malware Families
M. Eren
Ryan Barron
Manish Bhattarai
Selma Wanna
N. Solovyev
Kim Ø. Rasmussen
Boian S. Alexandrov
Charles K. Nicholas
129
1
0
04 Mar 2024
ImageNet-Hard: The Hardest Images Remaining from a Study of the Power of
  Zoom and Spatial Biases in Image Classification
ImageNet-Hard: The Hardest Images Remaining from a Study of the Power of Zoom and Spatial Biases in Image ClassificationNeural Information Processing Systems (NeurIPS), 2023
Mohammad Reza Taesiri
Giang Nguyen
Sarra Habchi
Cor-Paul Bezemer
Anh Totti Nguyen
VLM
224
26
0
11 Apr 2023
Steerable Equivariant Representation Learning
Steerable Equivariant Representation Learning
Sangnie Bhardwaj
Willie McClinton
Tongzhou Wang
Guillaume Lajoie
Chen Sun
Phillip Isola
Dilip Krishnan
OODLLMSV
149
5
0
22 Feb 2023
Rethinking and Recomputing the Value of Machine Learning Models
Rethinking and Recomputing the Value of Machine Learning ModelsArtificial Intelligence Review (Artif Intell Rev), 2022
Burcu Sayin
Fabio Casati
Baptiste Caramiaux
Andrea Passerini
Xinyue Chen
HAI
47
1
0
30 Sep 2022
Confidence Calibration with Bounded Error Using Transformations
Confidence Calibration with Bounded Error Using Transformations
Sooyong Jang
Radoslav Ivanov
Insup Lee
James Weimer
UQCV
84
3
0
25 Feb 2021
Better Aggregation in Test-Time Augmentation
Better Aggregation in Test-Time AugmentationIEEE International Conference on Computer Vision (ICCV), 2020
Divya Shanmugam
Davis W. Blalock
Guha Balakrishnan
John Guttag
ViT
163
175
0
23 Nov 2020
Improving Classifier Confidence using Lossy Label-Invariant
  Transformations
Improving Classifier Confidence using Lossy Label-Invariant Transformations
Sooyong Jang
Insup Lee
James Weimer
UQCV
104
7
0
09 Nov 2020
1