Image Classification on CIFAR-10, 40 Labels

Metric: Percentage error (lower is better)

LeaderboardDataset

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#	Model↕	Percentage error▲	Extra Data	Paper	Date↕	Code
1	SemiOccam	3.51	No	ViTSGMM: A Robust Semi-Supervised Image Recognit...	2025-06-04	Code
2	FreeMatch	4.9	No	FreeMatch: Self-adaptive Thresholding for Semi-s...	2022-05-15	Code
3	NP-Match	4.91	No	NP-Match: When Neural Processes meet Semi-Superv...	2022-07-03	Code
4	RelationMatch	4.96	No	RelationMatch: Matching In-batch Relationships f...	2023-05-17	Code
5	ShrinkMatch	5.08	No	Shrinking Class Space for Enhanced Certainty in ...	2023-08-13	Code
6	DebiasPL (w/ FixMatch)	5.4	No	Debiased Learning from Naturally Imbalanced Pseu...	2022-01-05	Code
7	SimMatch	5.6	No	SimMatch: Semi-supervised Learning with Similari...	2022-03-14	Code
8	FixMatch+CR	5.69	No	Contrastive Regularization for Semi-Supervised L...	2022-01-17	-
9	MutexMatch (k=0.6C)	5.79	No	MutexMatch: Semi-Supervised Learning with Mutex-...	2022-03-27	Code
10	FixMatch-USL-T	6.5	No	Unsupervised Selective Labeling for More Effecti...	2021-10-06	Code
11	Super-SST (ViT-Small)	9.59	No	SST: Self-training with Self-adaptive Thresholdi...	2025-05-31	-
12	UL-Hopfield (ULH)	16.9	No	Unsupervised Learning using Pretrained CNN and A...	2018-05-02	-
13	ReMixMatch	19.1	No	ReMixMatch: Semi-Supervised Learning with Distri...	2019-11-21	Code

#1SemiOccamSOTA
3.51
Percentage error· 2025-06-04
ViTSGMM: A Robust Semi-Supervised Image Recognition Network Using Sparse Labels Code
#2FreeMatchSOTA
4.9
Percentage error· 2022-05-15
FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning Code
#3NP-Match
4.91
Percentage error· 2022-07-03
NP-Match: When Neural Processes meet Semi-Supervised Learning Code
#4RelationMatch
4.96
Percentage error· 2023-05-17
RelationMatch: Matching In-batch Relationships for Semi-supervised Learning Code
#5ShrinkMatch
5.08
Percentage error· 2023-08-13
Shrinking Class Space for Enhanced Certainty in Semi-Supervised Learning Code
#6DebiasPL (w/ FixMatch)SOTA
5.4
Percentage error· 2022-01-05
Debiased Learning from Naturally Imbalanced Pseudo-Labels Code
#7SimMatch
5.6
Percentage error· 2022-03-14
SimMatch: Semi-supervised Learning with Similarity Matching Code
#8FixMatch+CR
5.69
Percentage error· 2022-01-17
Contrastive Regularization for Semi-Supervised Learning
#9MutexMatch (k=0.6C)
5.79
Percentage error· 2022-03-27
MutexMatch: Semi-Supervised Learning with Mutex-Based Consistency Regularization Code
#10FixMatch-USL-TSOTA
6.5
Percentage error· 2021-10-06
Unsupervised Selective Labeling for More Effective Semi-Supervised Learning Code
#11Super-SST (ViT-Small)
9.59
Percentage error· 2025-05-31
SST: Self-training with Self-adaptive Thresholding for Semi-supervised Learning
#12UL-Hopfield (ULH)SOTA
16.9
Percentage error· 2018-05-02
Unsupervised Learning using Pretrained CNN and Associative Memory Bank
#13ReMixMatch
19.1
Percentage error· 2019-11-21
ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring Code