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

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Showing 41–50 of 171 papers

Title	Date	Tasks	Status	Hype
F-PABEE: Flexible-patience-based Early Exiting for Single-label and Multi-label text Classification Tasks	May 21, 2023	Multi-Label ClassificationMUlTI-LABEL-ClASSIFICATION	—Unverified	0
An Exploration of Encoder-Decoder Approaches to Multi-Label Classification for Legal and Biomedical Text	May 9, 2023	ClassificationDecoder	CodeCode Available	1
What Do Patients Say About Their Disease Symptoms? Deep Multilabel Text Classification With Human-in-the-Loop Curation for Automatic Labeling of Patient Self Reports of Problems	May 8, 2023	Multilabel Text ClassificationMulti Label Text Classification	—Unverified	0
Label Dependencies-aware Set Prediction Networks for Multi-label Text Classification	Apr 14, 2023	Multi Label Text ClassificationMulti-Label Text Classification	—Unverified	0
Adopting the Multi-answer Questioning Task with an Auxiliary Metric for Extreme Multi-label Text Classification Utilizing the Label Hierarchy	Mar 2, 2023	ClassificationExtreme Multi-Label Classification	—Unverified	0
The Effect of Metadata on Scientific Literature Tagging: A Cross-Field Cross-Model Study	Feb 7, 2023	Language ModellingMulti Label Text Classification	CodeCode Available	1
CinPatent: Datasets for Patent Classification	Dec 23, 2022	ClassificationMulti Label Text Classification	—Unverified	0
Automated ICD Coding using Extreme Multi-label Long Text Transformer-based Models	Dec 12, 2022	Multi Label Text ClassificationMulti-Label Text Classification	CodeCode Available	0
Harnessing label semantics to extract higher performance under noisy label for Company to Industry matching	Dec 3, 2022	AI AgentMulti Label Text Classification	—Unverified	0
An Effective Deployment of Contrastive Learning in Multi-label Text Classification	Dec 1, 2022	ClassificationContrastive Learning	—Unverified	0

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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