Papers Multi-Label Text Classification
“Multi-Label Text Classification” 태그가 달린 논문 181편 · 필터 해제
Long-tailed Extreme Multi-label Text Classification with Generated Pseudo Label Descriptions
Extreme Multi-label Text Classification (XMTC) has been a tough challenge in machine learning research and applications due to the sheer sizes of the label spaces and the severe data scarce problem associated with the lo…
Multi Label Text ClassificationMulti-Label Text ClassificationPseudo LabelRetrieval+2Exploiting Local and Global Features in Transformer-based Extreme Multi-label Text Classification
Extreme multi-label text classification (XMTC) is the task of tagging each document with the relevant labels from a very large space of predefined categories. Recently, large pre-trained Transformer models have made sign…
Multi Label Text ClassificationMulti-Label Text Classificationtext-classificationText ClassificationMetadata-Induced Contrastive Learning for Zero-Shot Multi-Label Text Classification
Large-scale multi-label text classification (LMTC) aims to associate a document with its relevant labels from a large candidate set. Most existing LMTC approaches rely on massive human-annotated training data, which are …
Contrastive LearningMulti Label Text ClassificationMulti-Label Text Classificationtext-classification+2Multi-relation Message Passing for Multi-label Text Classification
A well-known challenge associated with the multi-label classification problem is modelling dependencies between labels. Most attempts at modelling label dependencies focus on co-occurrences, ignoring the valuable informa…
Classificationimage-classificationImage ClassificationMulti-Label Classification+7Extreme Zero-Shot Learning for Extreme Text Classification
The eXtreme Multi-label text Classification (XMC) problem concerns finding most relevant labels for an input text instance from a large label set. However, the XMC setup faces two challenges: (1) it is not generalizable …
ClassificationMulti Label Text ClassificationMulti-Label Text Classificationtext-classification+2Multi-Aspect co-Attentional Collaborative Filtering for Extreme Multi-label Text Classification
This work proposes a general and effective architecture for the extreme multi-label text classification (XMTC), and reformate the learning task to an interaction function between document and label. Recently, there are m…
Collaborative FilteringMulti Label Text ClassificationMulti-Label Text Classificationtext-classification+1HCL-MTC Hierarchical Contrastive Learning for Multi-label Text Classification
Multi-label text classification is a big challenging subtask in text classification, where labels generally form a tree structure. Existing solutions learn the label tree structure in a shallow manner and ignore the dist…
ClassificationContrastive LearningMulti Label Text ClassificationMulti-Label Text Classification+3GUDN: A novel guide network with label reinforcement strategy for extreme multi-label text classification
In natural language processing, extreme multi-label text classification is an emerging but essential task. The problem of extreme multi-label text classification (XMTC) is to recall some of the most relevant labels for a…
4kMulti Label Text ClassificationMulti-Label Text Classificationtext-classification+1Predicting Job Titles from Job Descriptions with Multi-label Text Classification
Finding a suitable job and hunting for eligible candidates are important to job seeking and human resource agencies. With the vast information about job descriptions, employees and employers need assistance to automatica…
Multi-Label ClassificationMUlTI-LABEL-ClASSIFICATIONMulti Label Text ClassificationMulti-Label Text Classification+2Extreme Zero-Shot Learning for Extreme Text Classification
The eXtreme Multi-label text Classification (XMC) problem concerns finding most relevant labels for an input text instance from a large label set. However, the XMC setup faces two challenges: (1) it is not generalizable …
ClassificationMulti Label Text ClassificationMulti-Label Text Classificationtext-classification+2Khmer Text Classification Using Word Embedding and Neural Networks
Text classification is one of the fundamental tasks in natural language processing to label an open-ended text and is useful for various applications such as sentiment analysis. In this paper, we discuss various classifi…
ClassificationMulti Label Text ClassificationMulti-Label Text ClassificationSentiment Analysis+2MUCIC at ComMA@ICON: Multilingual Gender Biased and Communal Language Identification Using N-grams and Multilingual Sentence Encoders
Social media analytics are widely being explored by researchers for various applications. Prominent among them are identifying and blocking abusive contents especially targeting individuals and communities, for various r…
BlockingLanguage IdentificationMulti Label Text ClassificationMulti-Label Text Classification+3Zero-Shot Cross-Lingual Transfer in Legal Domain Using Transformer Models
Zero-shot cross-lingual transfer is an important feature in modern NLP models and architectures to support low-resource languages. In this work, We study zero-shot cross-lingual transfer from English to French and German…
ClassificationCross-Lingual TransferLanguage ModelingLanguage Modelling+6Extreme Multi-label Text Classification with Pseudo Label Descriptions
Extreme multi-label text classification (XMTC) is the task of tagging each document with the relevant labels in a large predefined label space, where the label frequency distribution is often highly skewed. That is, a l…
ClassificationMulti Label Text ClassificationMulti-Label Text ClassificationPseudo Label+2Extreme Multi-label Text Classification with Multi-layer Experts
Extreme multi-label text classification (XMTC) is the task of tagging each document with the relevant labels from a very large space of predefined categories, which presents an open challenge in the recent development of…
ClassificationMulti Label Text ClassificationMulti-Label Text Classificationtext-classification+1Co-attention network with label embedding for text classification
Most existing methods for text classification focus on extracting a highly discriminative text representation, which, however, is typically computationally inefficient. To alleviate this issue, label embedding frameworks…
ClassificationMulti-class ClassificationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATION+4Hierarchical Multi-label Text Classification with Horizontal and Vertical Category Correlations
Hierarchical multi-label text classification (HMTC) deals with the challenging task where an instance can be assigned to multiple hierarchically structured categories at the same time. The majority of prior studies eithe…
Multi Label Text ClassificationMulti-Label Text Classificationtext-classificationText ClassificationMeta-LMTC: Meta-Learning for Large-Scale Multi-Label Text Classification
Large-scale multi-label text classification (LMTC) tasks often face long-tailed label distributions, where many labels have few or even no training instances. Although current methods can exploit prior knowledge to handl…
Meta-LearningMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATIONMulti Label Text Classification+3Multi-Label Text Classification by Graph Neural Network with Mixing Operations
Multi-label text classification is one of the fundamental tasks in natural language processing. Recently, the graph convolution network (GCN) is leveraged to boost the performance of such a task. However, the best way fo…
Graph Neural NetworkMulti Label Text ClassificationMulti-Label Text ClassificationRepresentation Learning+2Re-evaluating Extreme Multi-label Text Classification Methods in Tail Label Prediction
Extreme multi-label text classification (XMTC) is the task of tagging each document with the relevant labels in a very large set of predefined category labels. The most challenging part of the problem is due to a highly …
Multi Label Text ClassificationMulti-Label Text Classificationtext-classificationText Classification