SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–10 of 171 papers

TitleStatusHype
KDH-MLTC: Knowledge Distillation for Healthcare Multi-Label Text Classification—0
QUAD-LLM-MLTC: Large Language Models Ensemble Learning for Healthcare Text Multi-Label Classification—0
Task-Informed Anti-Curriculum by Masking Improves Downstream Performance on TextCode0
Retrieval-augmented Encoders for Extreme Multi-label Text Classification—0
Hierarchical Text Classification (HTC) vs. eXtreme Multilabel Classification (XML): Two Sides of the Same MedalCode0
A Similarity-Based Oversampling Method for Multi-label Imbalanced Text Data—0
Large Language Models for Patient Comments Multi-Label Classification—0
Don't Just Pay Attention, PLANT It: Transfer L2R Models to Fine-tune Attention in Extreme Multi-Label Text Classification—0
A Novel Method to Metigate Demographic and Expert Bias in ICD Coding with Causal Inference—0
Similarity-Dissimilarity Loss for Multi-label Supervised Contrastive LearningCode0
Show:102550
← PrevPage 1 of 18Next →
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
1LAHAP@194.87—Unverified