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Multi-Label Text Classification

According to Wikipedia "In machine learning, multi-label classification and the strongly related problem of multi-output classification are variants of the classification problem where multiple labels may be assigned to each instance. Multi-label classification is a generalization of multiclass classification, which is the single-label problem of categorizing instances into precisely one of more than two classes; in the multi-label problem there is no constraint on how many of the classes the instance can be assigned to."

Papers

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Showing 51–100 of 171 papers

TitleStatusHype
Pairwise Instance Relation Augmentation for Long-tailed Multi-label Text Classification—0
Hierarchical Multi-Label Classification of Scientific DocumentsCode1
Enhancing Chinese Multi-Label Text Classification Performance with Response-based Knowledge Distillation—0
CascadeXML: Rethinking Transformers for End-to-end Multi-resolution Training in Extreme Multi-label ClassificationCode0
BERT-Flow-VAE: A Weakly-supervised Model for Multi-Label Text Classification—0
OTSeq2Set: An Optimal Transport Enhanced Sequence-to-Set Model for Extreme Multi-label Text ClassificationCode1
A Multi-Dimensional, Cross-Domain and Hierarchy-Aware Neural Architecture for ISO-Standard Dialogue Act Tagging—0
生成模型在层次结构极限多标签文本分类中的应用(Generation Model for Hierarchical Extreme Multi-label Text Classification)—0
Correlation Networks for Extreme Multi-label Text ClassificationCode1
HITMI&T at SemEval-2022 Task 4: Investigating Task-Adaptive Pretraining And Attention Mechanism On PCL Detection—0
SSN_NLP_MLRG at SemEval-2022 Task 4: Ensemble Learning strategies to detect Patronizing and Condescending Language—0
Even the Simplest Baseline Needs Careful Re-investigation: A Case Study on XML-CNN—0
Investigating Active Learning Sampling Strategies for Extreme Multi Label Text Classification—0
Exploiting Dynamic and Fine-grained Semantic Scope for Extreme Multi-label Text Classification—0
Exploiting Global and Local Hierarchies for Hierarchical Text ClassificationCode1
RaFoLa: A Rationale-Annotated Corpus for Detecting Indicators of Forced Labour—0
Contrastive Learning-Enhanced Nearest Neighbor Mechanism for Multi-Label Text Classification—0
HFT-ONLSTM: Hierarchical and Fine-Tuning Multi-label Text Classification—0
An Ensemble Learning Based Approach to Multi-label Power Text Classification for Fault-type Recognition—0
Are We Really Making Much Progress in Text Classification? A Comparative ReviewCode1
Long-tailed Extreme Multi-label Text Classification with Generated Pseudo Label Descriptions—0
Exploiting Local and Global Features in Transformer-based Extreme Multi-label Text Classification—0
Metadata-Induced Contrastive Learning for Zero-Shot Multi-Label Text ClassificationCode1
Multi-relation Message Passing for Multi-label Text ClassificationCode0
HCL-MTC Hierarchical Contrastive Learning for Multi-label Text Classification—0
Multi-Aspect co-Attentional Collaborative Filtering for Extreme Multi-label Text Classification—0
Extreme Zero-Shot Learning for Extreme Text Classification—0
GUDN: A novel guide network with label reinforcement strategy for extreme multi-label text classificationCode0
Predicting Job Titles from Job Descriptions with Multi-label Text ClassificationCode0
Extreme Zero-Shot Learning for Extreme Text ClassificationCode0
Khmer Text Classification Using Word Embedding and Neural Networks—0
MUCIC at ComMA@ICON: Multilingual Gender Biased and Communal Language Identification Using N-grams and Multilingual Sentence Encoders—0
Zero-Shot Cross-Lingual Transfer in Legal Domain Using Transformer ModelsCode0
Extreme Multi-label Text Classification with Multi-layer Experts—0
Extreme Multi-label Text Classification with Pseudo Label Descriptions—0
Co-attention network with label embedding for text classificationCode1
Meta-LMTC: Meta-Learning for Large-Scale Multi-Label Text Classification—0
Hierarchical Multi-label Text Classification with Horizontal and Vertical Category Correlations—0
Re-evaluating Extreme Multi-label Text Classification Methods in Tail Label Prediction—0
Multi-Label Text Classification by Graph Neural Network with Mixing Operations—0
Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text ClassificationCode0
Modeling label correlations implicitly through latent label encodings for multi-label text classification—0
CoPHE: A Count-Preserving Hierarchical Evaluation Metric in Large-Scale Multi-Label Text ClassificationCode0
Balancing Methods for Multi-label Text Classification with Long-Tailed Class DistributionCode1
A Dutch Dataset for Cross-lingual Multilabel Toxicity Detection—0
Label-Specific Dual Graph Neural Network for Multi-Label Text Classification—0
ECLARE: Extreme Classification with Label Graph CorrelationsCode1
Small-Text: Active Learning for Text Classification in PythonCode0
Label prompt for multi-label text classification—0
On Evaluation and Improvement of Tail Label Performance for Multi-label Text Classification—0
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All datasetsCC3M-TagMaskReuters-21578AAPDFreecodeBVICTOREUR-LexMVICTOR (theme)SVICTOR (theme)MIMIC-IIIMIMIC-III-50Amazon-12KDataset of Propaganda Techniques of the State-Sponsored Information Operation of the People's Republic of China

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TTD (w/ fine-tuning)Precision88.3—Unverified
2TTD (w/o fine-tuning)Precision82.9—Unverified
3Qwen-72BPrecision69.3—Unverified
4NLTKPrecision59.8—Unverified
5Vicuna-33BPrecision52.7—Unverified
6Vicuna-7BPrecision44.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CB-NTRMicro-F190.74—Unverified
2NTR-FLMicro-F190.7—Unverified
3DBMicro-F190.62—Unverified
4MAGNETMicro-F189.9—Unverified
5CNLEMicro-F189.9—Unverified
6VLAWEMicro-F189.3—Unverified
#ModelMetricClaimedVerifiedStatus
1LSANP@185.28—Unverified
2LAHAP@184.48—Unverified
3LW-PTMicro F172.8—Unverified
4CNLEMicro F171.7—Unverified
5MAGNETF169.6—Unverified
#ModelMetricClaimedVerifiedStatus
1TagBERTF1-score46—Unverified
2TagCNNF1-score45.3—Unverified
3TagMulRecF1-score36.4—Unverified
4EnTagRecF1-score36—Unverified
5FastTagRecF1-score33.2—Unverified
#ModelMetricClaimedVerifiedStatus
1XGBoostAverage F10.88—Unverified
2SVMAverage F10.78—Unverified
3NBAverage F10.63—Unverified
#ModelMetricClaimedVerifiedStatus
1bert-baseP@568.7—Unverified
2NLP-CapP@552.83—Unverified
3LAHAP@550.71—Unverified
#ModelMetricClaimedVerifiedStatus
1XGBoostAverage F10.89—Unverified
2SVMAverage F10.66—Unverified
3NBAverage F10.38—Unverified
#ModelMetricClaimedVerifiedStatus
1XGBoostAverage F10.89—Unverified
2SVMAverage F10.82—Unverified
3NBAverage F10.51—Unverified
#ModelMetricClaimedVerifiedStatus
1HLANAUC0.92—Unverified
2Feed-forward NNPrecision0.25—Unverified
#ModelMetricClaimedVerifiedStatus
1D2SBERT using Sequence AttentionMicro-F168.56—Unverified
2HLANMicro-F164.1—Unverified
#ModelMetricClaimedVerifiedStatus
1LAHAP@194.87—Unverified
#ModelMetricClaimedVerifiedStatus
1Bert1:1 Accuracy0.8—Unverified
#ModelMetricClaimedVerifiedStatus
1LAHAP@154.38—Unverified
#ModelMetricClaimedVerifiedStatus
1DECAFPrecision@138.4—Unverified
#ModelMetricClaimedVerifiedStatus
1ECLAREPrecision@140.74—Unverified
#ModelMetricClaimedVerifiedStatus
1HiddeNMacro-F147.3—Unverified
#ModelMetricClaimedVerifiedStatus
1MAGNETMicro-F188.5—Unverified
#ModelMetricClaimedVerifiedStatus
1MAGNETMicro-F156.8—Unverified
#ModelMetricClaimedVerifiedStatus
1BERTF166.83—Unverified
#ModelMetricClaimedVerifiedStatus
1LAHAP@184.18—Unverified