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Multi-Label Classification

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Multi-Label Classification is the supervised learning problem where an instance may be associated with multiple labels. This is an extension of single-label classification (i.e., multi-class, or binary) where each instance is only associated with a single class label.

Source: Deep Learning for Multi-label Classification

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/thunguyen177/iul-cbmi

공식 코드

Imputation using training labels and classification via label imputation

https://github.com/tianqi-py/agale

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AGALE: A Graph-Aware Continual Learning Evaluation Framework

https://github.com/tianqi-py/mlgnc

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A data-centric approach for assessing progress of Graph Neural Networks

https://github.com/tijana-zrnic/cross-ppi

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Cross-Prediction-Powered Inference

https://github.com/tooploox/plugin-networks

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Plugin Networks for Inference under Partial Evidence

https://github.com/turkunlp/multilingual-core

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Automatic register identification for the open web using multilingual deep learning

https://github.com/uber/ludwig

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Ludwig: a type-based declarative deep learning toolbox

https://github.com/ubiwell/sesame-llms-ground-truth-code

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SeSaMe: A Framework to Simulate Self-Reported Ground Truth for Mental Health Sensing Studies

https://github.com/uclanlp/ILPLearning

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An Integer Linear Programming Framework for Mining Constraints from Data

https://github.com/uknownpioneer/GSMLP-SMLC

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Unsupervised Person Re-identification via Multi-Label Prediction and Classification based on Graph-Structural Insight

https://github.com/um2ii/quantum-cxr

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Expanding the Horizon: Enabling Hybrid Quantum Transfer Learning for Long-Tailed Chest X-Ray Classification

https://github.com/unslothai/unsloth

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Lotus at SemEval-2025 Task 11: RoBERTa with Llama-3 Generated Explanations for Multi-Label Emotion Classification

https://github.com/uva-dsa/dkec

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DKEC: Domain Knowledge Enhanced Multi-Label Classification for Diagnosis Prediction

https://github.com/vamosc/colearning-meet-stitchup

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Co-Learning Meets Stitch-Up for Noisy Multi-label Visual Recognition

https://github.com/vedantpalit/WellDunn

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WellDunn: On the Robustness and Explainability of Language Models and Large Language Models in Identifying Wellness Dimensions

https://github.com/vioshyvo/a-multilabel-classification-framework

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A Multilabel Classification Framework for Approximate Nearest Neighbor Search

https://github.com/virtuosoresearch/scalablemtl

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Scalable Multitask Learning Using Gradient-based Estimation of Task Affinity

https://github.com/vithyayogarajan/Medical-Domain-Specific-Language-Models

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Improving Predictions of Tail-end Labels using Concatenated BioMed-Transformers for Long Medical Documents

https://github.com/vithyayogarajan/covid-19-patient-shielding

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Predicting COVID-19 Patient Shielding: A Comprehensive Study

https://github.com/voyazici/orderless-rnn-classification

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Orderless Recurrent Models for Multi-label Classification

https://github.com/voyazici/visual-transformers-classification

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Visual Transformers with Primal Object Queries for Multi-Label Image Classification

https://github.com/vyzuer/ALTReco

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Adversarial Learning for Personalized Tag Recommendation

https://github.com/web3se-lab/web3-sekit

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Deep Smart Contract Intent Detection

https://github.com/wennyxy/dino-mc

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Extending global-local view alignment for self-supervised learning with remote sensing imagery

https://github.com/wesleyhsieh0806/ss-prl

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Self-Supervised Pyramid Representation Learning for Multi-Label Visual Analysis and Beyond

https://github.com/whaleloops/KEPT

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Knowledge Injected Prompt Based Fine-tuning for Multi-label Few-shot ICD Coding

https://github.com/wren93/hicu-icd

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HiCu: Leveraging Hierarchy for Curriculum Learning in Automated ICD Coding

https://github.com/wushanshan/L1AE

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Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling

https://github.com/wutong16/DistributionBalancedLoss

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Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets

https://github.com/wxr99/cut-replay

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Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning

https://github.com/wzh9969/contrastive-htc

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Incorporating Hierarchy into Text Encoder: a Contrastive Learning Approach for Hierarchical Text Classification

https://github.com/wzh9969/hiadv

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Utilizing Local Hierarchy with Adversarial Training for Hierarchical Text Classification

https://github.com/wzh9969/hpt

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HPT: Hierarchy-aware Prompt Tuning for Hierarchical Text Classification

https://github.com/wzhouad/ATLOP

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Document-Level Relation Extraction with Adaptive Thresholding and Localized Context Pooling

https://github.com/xinyu1205/robust-loss-mlml

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Simple and Robust Loss Design for Multi-Label Learning with Missing Labels

https://github.com/xiongyiheng/Prior-RadGraphFormer

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Prior-RadGraphFormer: A Prior-Knowledge-Enhanced Transformer for Generating Radiology Graphs from X-Rays

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.