Multi Label Text Classification
44 papers with code • 2 benchmarks • 4 datasets
Benchmarks
These leaderboards are used to track progress in Multi Label Text Classification
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Libraries
Use these libraries to find Multi Label Text Classification models and implementations
MNIST
GoEmotions
CARER
HateScore
Most implemented papers
Correlation Networks for Extreme Multi-label Text Classification
XunGuangxu/CorNet
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Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining 2022
This paper develops the Correlation Networks (CorNet) architecture for the extreme multi-label text classification (XMTC) task, where the objective is to tag an input text sequence with the most relevant subset of labels from an extremely large label set.
MAGNET: Multi-Label Text Classification using Attention-based Graph Neural Network
The graph attention network uses a feature matrix and a correlation matrix to capture and explore the crucial dependencies between the labels and generate classifiers for the task.
Multi-Label Text Classification using Attention-based Graph Neural Network
adrinta/MAGNET
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The graph attention network uses a feature matrix and a correlation matrix to capture and explore the crucial dependencies between the labels and generate classifiers for the task.
Regularizing Model Complexity and Label Structure for Multi-Label Text Classification
Multi-label text classifiers need to be carefully regularized to prevent the severe over-fitting in the high dimensional space, and also need to take into account label dependencies in order to make accurate predictions under uncertainty.
Semantic-Unit-Based Dilated Convolution for Multi-Label Text Classification
lancopku/SU4MLC
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EMNLP 2018
We propose a novel model for multi-label text classification, which is based on sequence-to-sequence learning.
Few-Shot and Zero-Shot Multi-Label Learning for Structured Label Spaces
Furthermore, we develop few- and zero-shot methods for multi-label text classification when there is a known structure over the label space, and evaluate them on two publicly available medical text datasets: MIMIC II and MIMIC III.
Label-aware Document Representation via Hybrid Attention for Extreme Multi-Label Text Classification
HX-idiot/Hybrid_Attention_XML
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Extreme multi-label text classification (XMTC) aims at tagging a document with most relevant labels from an extremely large-scale label set.
Large-Scale Multi-Label Text Classification on EU Legislation
iliaschalkidis/lmtc-eurlex57k
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ACL 2019
We consider Large-Scale Multi-Label Text Classification (LMTC) in the legal domain.
Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification
In this paper, we propose a novel hierarchical taxonomy-aware and attentional graph capsule recurrent CNNs framework for large-scale multi-label text classification.
Hierarchical Multi-label Classification of Text with Capsule Networks
Capsule networks have been shown to demonstrate good performance on structured data in the area of visual inference.
