Multilabel Text Classification
5 papers with code • 1 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Multilabel Text Classification
| Trend | Dataset | Best Model | Paper | Code | Compare |
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HumSet
TuPyE-Dataset
Most implemented papers
CAWA: An Attention-Network for Credit Attribution
Experiments on the credit attribution task on a variety of datasets show that the sentence class labels generated by CAWA outperform the competing approaches.
Establishing Baselines for Text Classification in Low-Resource Languages
jcblaisecruz02/Filipino-Text-Benchmarks
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We analyze our pretrained model's degradation speeds and look towards the use of this method for comparing models aimed at operating within the low-resource setting.
Adversarial Examples for Extreme Multilabel Text Classification
Extreme Multilabel Text Classification (XMTC) is a text classification problem in which, (i) the output space is extremely large, (ii) each data point may have multiple positive labels, and (iii) the data follows a strongly imbalanced distribution.
HumSet: Dataset of Multilingual Information Extraction and Classification for Humanitarian Crisis Response
Timely and effective response to humanitarian crises requires quick and accurate analysis of large amounts of text data - a process that can highly benefit from expert-assisted NLP systems trained on validated and annotated data in the humanitarian response domain.
A Two-Stage Decoder for Efficient ICD Coding
Clinical notes in healthcare facilities are tagged with the International Classification of Diseases (ICD) code; a list of classification codes for medical diagnoses and procedures.
