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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 1–10 of 171 papers

Title	Date	Tasks	Status	Hype	Score
Qwen Technical Report	Sep 28, 2023	Language ModelingLanguage Modelling	CodeCode Available	6	5
Correlation Networks for Extreme Multi-label Text Classification	Aug 23, 2022	ClassificationMulti Label Text Classification	CodeCode Available	1	5
Prompt Tuned Embedding Classification for Multi-Label Industry Sector Allocation	Sep 21, 2023	BenchmarkingClassification	CodeCode Available	1	5
Co-attention network with label embedding for text classification	Nov 4, 2021	ClassificationMulti-class Classification	CodeCode Available	1	5
AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification	Nov 1, 2018	General ClassificationMulti-Label Text Classification	CodeCode Available	1	5
Are We Really Making Much Progress in Text Classification? A Comparative Review	Apr 8, 2022	ClassificationDecoder	CodeCode Available	1	5
Balancing Methods for Multi-label Text Classification with Long-Tailed Class Distribution	Sep 10, 2021	Document ClassificationMulti-Label Text Classification	CodeCode Available	1	5
An Exploration of Encoder-Decoder Approaches to Multi-Label Classification for Legal and Biomedical Text	May 9, 2023	ClassificationDecoder	CodeCode Available	1	5
An Empirical Study on Large-Scale Multi-Label Text Classification Including Few and Zero-Shot Labels	Oct 4, 2020	Multi-Label ClassificationMUlTI-LABEL-ClASSIFICATION	CodeCode Available	1	5
Compositional Generalization for Multi-label Text Classification: A Data-Augmentation Approach	Dec 18, 2023	ClassificationData Augmentation	CodeCode Available	1	5

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All datasets CC3M-TagMask Reuters-21578 AAPD Freecode BVICTOR EUR-Lex MVICTOR (theme)SVICTOR (theme)MIMIC-III MIMIC-III-50 Amazon-12K Dataset of Propaganda Techniques of the State-Sponsored Information Operation of the People's Republic of China

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	TTD (w/ fine-tuning)	Precision	88.3	—	Unverified
2	TTD (w/o fine-tuning)	Precision	82.9	—	Unverified
3	Qwen-72B	Precision	69.3	—	Unverified
4	NLTK	Precision	59.8	—	Unverified
5	Vicuna-33B	Precision	52.7	—	Unverified
6	Vicuna-7B	Precision	44.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CB-NTR	Micro-F1	90.74	—	Unverified
2	NTR-FL	Micro-F1	90.7	—	Unverified
3	DB	Micro-F1	90.62	—	Unverified
4	MAGNET	Micro-F1	89.9	—	Unverified
5	CNLE	Micro-F1	89.9	—	Unverified
6	VLAWE	Micro-F1	89.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LSAN	P@1	85.28	—	Unverified
2	LAHA	P@1	84.48	—	Unverified
3	LW-PT	Micro F1	72.8	—	Unverified
4	CNLE	Micro F1	71.7	—	Unverified
5	MAGNET	F1	69.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TagBERT	F1-score	46	—	Unverified
2	TagCNN	F1-score	45.3	—	Unverified
3	TagMulRec	F1-score	36.4	—	Unverified
4	EnTagRec	F1-score	36	—	Unverified
5	FastTagRec	F1-score	33.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	XGBoost	Average F1	0.88	—	Unverified
2	SVM	Average F1	0.78	—	Unverified
3	NB	Average F1	0.63	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	bert-base	P@5	68.7	—	Unverified
2	NLP-Cap	P@5	52.83	—	Unverified
3	LAHA	P@5	50.71	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	XGBoost	Average F1	0.89	—	Unverified
2	SVM	Average F1	0.66	—	Unverified
3	NB	Average F1	0.38	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	XGBoost	Average F1	0.89	—	Unverified
2	SVM	Average F1	0.82	—	Unverified
3	NB	Average F1	0.51	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HLAN	AUC	0.92	—	Unverified
2	Feed-forward NN	Precision	0.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	D2SBERT using Sequence Attention	Micro-F1	68.56	—	Unverified
2	HLAN	Micro-F1	64.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LAHA	P@1	94.87	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Bert	1:1 Accuracy	0.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LAHA	P@1	54.38	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DECAF	Precision@1	38.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ECLARE	Precision@1	40.74	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HiddeN	Macro-F1	47.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MAGNET	Micro-F1	88.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MAGNET	Micro-F1	56.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BERT	F1	66.83	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LAHA	P@1	84.18	—	Unverified