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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
Imbalanced Multi-label Classification for Business-related Text with Moderately Large Label Spaces—0
Improved Neural Network-based Multi-label Classification with Better Initialization Leveraging Label Co-occurrence—0
HAXMLNet: Hierarchical Attention Network for Extreme Multi-Label Text Classification—0
A Debiased Nearest Neighbors Framework for Multi-Label Text Classification—0
Accurate Use of Label Dependency in Multi-Label Text Classification Through the Lens of Causality—0
Active learning for medical code assignment—0
A Deep Reinforced Sequence-to-Set Model for Multi-Label Text Classification—0
Adopting the Multi-answer Questioning Task with an Auxiliary Metric for Extreme Multi-label Text Classification Utilizing the Label Hierarchy—0
A Dutch Dataset for Cross-lingual Multilabel Toxicity Detection—0
Aggression Identification and Multi Lingual Word Embeddings—0
Joint Embedding of Words and Category Labels for Hierarchical Multi-label Text Classification—0
A Multi-Dimensional, Cross-Domain and Hierarchy-Aware Neural Architecture for ISO-Standard Dialogue Act Tagging—0
A multi-level multi-label text classification dataset of 19th century Ottoman and Russian literary and critical texts—0
An Ensemble Learning Based Approach to Multi-label Power Text Classification for Fault-type Recognition—0
A Novel Method to Metigate Demographic and Expert Bias in ICD Coding with Causal Inference—0
A Similarity-Based Oversampling Method for Multi-label Imbalanced Text Data—0
BdLAN:BERTdoc Label Attention Networks for Multi-label text classification—0
BERT-Flow-VAE: A Weakly-supervised Model for Multi-Label Text Classification—0
ChronosLex: Time-aware Incremental Training for Temporal Generalization of Legal Classification Tasks—0
Comparison of Machine Learning Methods for Multi-label Classification of Nursing Education and Licensure Exam Questions—0
Contrastive Learning-Enhanced Nearest Neighbor Mechanism for Multi-Label Text Classification—0
DEFTri: A Few-Shot Label Fused Contextual Representation Learning For Product Defect Triage in e-Commerce—0
Don't Just Pay Attention, PLANT It: Transfer L2R Models to Fine-tune Attention in Extreme Multi-Label Text Classification—0
Empowering Interdisciplinary Research with BERT-Based Models: An Approach Through SciBERT-CNN with Topic Modeling—0
EMR Coding with Semi-Parametric Multi-Head Matching Networks—0
Enhancing Chinese Multi-Label Text Classification Performance with Response-based Knowledge Distillation—0
Even the Simplest Baseline Needs Careful Re-investigation: A Case Study on XML-CNN—0
Exploiting Dynamic and Fine-grained Semantic Scope for Extreme Multi-label Text Classification—0
Exploiting Local and Global Features in Transformer-based Extreme Multi-label Text Classification—0
Exploring Contrastive Learning for Long-Tailed Multi-Label Text Classification—0
Exploring space efficiency in a tree-based linear model for extreme multi-label classification—0
Extreme Multi-Label Legal Text Classification: A case study in EU Legislation—0
Extreme Multi-label Text Classification with Pseudo Label Descriptions—0
Extreme Multi-label Text Classification with Multi-layer Experts—0
Extreme Zero-Shot Learning for Extreme Text Classification—0
F-PABEE: Flexible-patience-based Early Exiting for Single-label and Multi-label text Classification Tasks—0
Generalized Zero-shot ICD Coding—0
Initializing neural networks for hierarchical multi-label text classification—0
Investigating Active Learning Sampling Strategies for Extreme Multi Label Text Classification—0
KDH-MLTC: Knowledge Distillation for Healthcare Multi-Label Text Classification—0
KeNet:Knowledge-enhanced Doc-Label Attention Network for Multi-label text classification—0
Khmer Text Classification Using Word Embedding and Neural Networks—0
Label Dependencies-aware Set Prediction Networks for Multi-label Text Classification—0
Label prompt for multi-label text classification—0
Label-Specific Dual Graph Neural Network for Multi-Label Text Classification—0
Large Language Models for Patient Comments Multi-Label Classification—0
Large-scale Multi-label Text Classification - Revisiting Neural Networks—0
Learning label-label correlations in Extreme Multi-label Classification via Label Features—0
CinPatent: Datasets for Patent Classification—0
LegalTurk Optimized BERT for Multi-Label Text Classification and NER—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