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Multi-Label Classification

multilabel graph classification with highest result

Papers

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Showing 601–625 of 1198 papers

TitleStatusHype
Order-Prompted Tag Sequence Generation for Video Tagging—0
ORIGAMI: A generative transformer architecture for predictions from semi-structured data—0
Orthogonal Multi-view Analysis by Successive Approximations via Eigenvectors—0
Overview of Tencent Multi-modal Ads Video Understanding Challenge—0
Overview of the 2013 ALTA Shared Task—0
PAIC at SemEval-2022 Task 5: Multi-Modal Misogynous Detection in MEMES with Multi-Task Learning And Multi-model Fusion—0
Parameter Selection: Why We Should Pay More Attention to It—0
Parity Partition Coding for Sharp Multi-Label Classification—0
PENCIL: Deep Learning with Noisy Labels—0
PercentMatch: Percentile-based Dynamic Thresholding for Multi-Label Semi-Supervised Classification—0
PiCkLe at SemEval-2022 Task 4: Boosting Pre-trained Language Models with Task Specific Metadata and Cost Sensitive Learning—0
P4E: Few-Shot Event Detection as Prompt-Guided Identification and Localization—0
PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood Aggregation—0
PINGAN Omini-Sinitic at SemEval-2022 Task 4: Multi-prompt Training for Patronizing and Condescending Language Detection—0
PLMCL: Partial-Label Momentum Curriculum Learning for Multi-Label Image Classification—0
PLM: Partial Label Masking for Imbalanced Multi-label Classification—0
Polyphonic audio event detection: multi-label or multi-class multi-task classification problem?—0
Pose Guided Attention for Multi-label Fashion Image Classification—0
Positive semidefinite support vector regression metric learning—0
Powerset multi-class cross entropy loss for neural speaker diarization—0
Predict and Constrain: Modeling Cardinality in Deep Structured Prediction—0
Predicting Event Time by Classifying Sub-Level Temporal Relations Induced from a Unified Representation of Time Anchors—0
Predicting potentially abusive clauses in Chilean terms of services with natural language processing—0
Predicting Useful Neighborhoods for Lazy Local Learning—0
Predicting User-specific Future Activities using LSTM-based Multi-label Classification—0
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All datasetsCheXpertMS-COCOPASCAL VOC 2007NUS-WIDEChestX-ray14OpenImages-v6PASCAL VOC 2012MLRSNetMRNetMIMIC-CXR

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CFT (ensemble) Macao Polytechnic UniversityAVERAGE AUC ON 14 LABEL0.93—Unverified
2Hierarchical-Learning-V1 (ensemble)AVERAGE AUC ON 14 LABEL0.93—Unverified
3DeepAUC-v1AVERAGE AUC ON 14 LABEL0.93—Unverified
4Conditional-Training-LSRAVERAGE AUC ON 14 LABEL0.93—Unverified
5Hierarchical-Learning-V4 (ensemble)AVERAGE AUC ON 14 LABEL0.93—Unverified
6YWW(ensemble)AVERAGE AUC ON 14 LABEL0.93—Unverified
7Hierarchical-Learning-V0 (ensemble)AVERAGE AUC ON 14 LABEL0.93—Unverified
8Conditional-Training-LSR-V1AVERAGE AUC ON 14 LABEL0.93—Unverified
9DeepCNNsGM(ensemble)AVERAGE AUC ON 14 LABEL0.93—Unverified
10Multi-Stage-Learning-CNN-V3 (ensemble)AVERAGE AUC ON 14 LABEL0.93—Unverified