SOTAVerified

Extreme Multi-Label Classification

Extreme Multi-Label Classification is a supervised learning problem where an instance may be associated with multiple labels. The two main problems are the unbalanced labels in the dataset and the amount of different labels.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–25 of 75 papers

TitleStatusHype
Efficient Text Encoders for Labor Market Analysis—0
Retrieval-augmented Encoders for Extreme Multi-label Text Classification—0
Prototypical Extreme Multi-label Classification with a Dynamic Margin Loss—0
Exploring space efficiency in a tree-based linear model for extreme multi-label classification—0
GraphEx: A Graph-based Extraction Method for Advertiser Keyphrase Recommendation—0
From Lazy to Prolific: Tackling Missing Labels in Open Vocabulary Extreme Classification by Positive-Unlabeled Sequence Learning—0
Semantic Operators: A Declarative Model for Rich, AI-based Data ProcessingCode5
Multi-label Learning with Random Circular VectorsCode0
UniDEC : Unified Dual Encoder and Classifier Training for Extreme Multi-Label Classification—0
Learning label-label correlations in Extreme Multi-label Classification via Label Features—0
In-Context Learning for Extreme Multi-Label ClassificationCode3
ICXML: An In-Context Learning Framework for Zero-Shot Extreme Multi-Label ClassificationCode0
Generalized test utilities for long-tail performance in extreme multi-label classificationCode0
Dense Retrieval as Indirect Supervision for Large-space Decision MakingCode0
Dual-Encoders for Extreme Multi-Label ClassificationCode0
Extreme Multi-Label Skill Extraction Training using Large Language Models—0
MDACE: MIMIC Documents Annotated with Code EvidenceCode0
PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood AggregationCode0
Extreme Classification for Answer Type Prediction in Question Answering—0
Adopting the Multi-answer Questioning Task with an Auxiliary Metric for Extreme Multi-label Text Classification Utilizing the Label Hierarchy—0
Cluster-Guided Label Generation in Extreme Multi-Label ClassificationCode1
Review of Extreme Multilabel Classification—0
CascadeXML: Rethinking Transformers for End-to-end Multi-resolution Training in Extreme Multi-label ClassificationCode0
Uncertainty in Extreme Multi-label Classification—0
ELIAS: End-to-End Learning to Index and Search in Large Output SpacesCode1
Show:102550
← PrevPage 1 of 3Next →

No leaderboard results yet.