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Multi-Task Learning

Multi-task learning aims to learn multiple different tasks simultaneously while maximizing performance on one or all of the tasks.

( Image credit: Cross-stitch Networks for Multi-task Learning )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 2261–2270 of 3687 papers

Title	Date	Tasks	Status	Hype
Detecting 32 Pedestrian Attributes for Autonomous Vehicles	Dec 4, 2020	AttributeAutonomous Driving	CodeCode Available	1
Learning Class-Transductive Intent Representations for Zero-shot Intent Detection	Dec 3, 2020	Intent DetectionMulti-Task Learning	CodeCode Available	1
Adapt-and-Adjust: Overcoming the Long-Tail Problem of Multilingual Speech Recognition	Dec 3, 2020	Language ModelingLanguage Modelling	—Unverified	0
Extracting Fractional Inspiratory Time from Electrocardiograms	Dec 2, 2020	Multi-Task Learning	—Unverified	0
Learning Spatial Attention for Face Super-Resolution	Dec 2, 2020	Face ParsingImage Super-Resolution	CodeCode Available	1
Chinese Grammatical Error Diagnosis with Graph Convolution Network and Multi-task Learning	Dec 1, 2020	Language ModelingLanguage Modelling	—Unverified	0
KanCMD: Kannada CodeMixed Dataset for Sentiment Analysis and Offensive Language Detection	Dec 1, 2020	Language IdentificationMulti-Task Learning	—Unverified	0
Exploiting Narrative Context and A Priori Knowledge of Categories in Textual Emotion Classification	Dec 1, 2020	Emotion ClassificationMulti-Task Learning	—Unverified	0
An Empirical Study on Multi-Task Learning for Text Style Transfer and Paraphrase Generation	Dec 1, 2020	Multi-Task LearningParaphrase Generation	—Unverified	0
Semi-supervised Multi-task Learning for Multi-label Fine-grained Sexism Classification	Dec 1, 2020	ClassificationMulti-Label Classification	CodeCode Available	0

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All datasets QM9 Cityscapes test NYUv2 OMNIGLOT CelebA UTKFace wireframe dataset

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	PCGrad	∆m%	125.7	—	Unverified
2	CAGrad	∆m%	112.8	—	Unverified
3	IMTL-G	∆m%	77.2	—	Unverified
4	Nash-MTL	∆m%	62	—	Unverified
5	BayesAgg-MTL	∆m%	53.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SwinMTL	mIoU	76.41	—	Unverified
2	Nash-MTL	mIoU	75.41	—	Unverified
3	MultiObjectiveOptimization	mIoU	66.63	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SwinMTL	Mean IoU	58.14	—	Unverified
2	Nash-MTL	Mean IoU	40.13	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Gumbel-Matrix Routing	Average Accuracy	93.52	—	Unverified
2	Mixture-of-Experts	Average Accuracy	92.19	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MGDA-UB	Error	8.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BayesAgg-MTL	delta_m	-2.23	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LETR	FH	83.3	—	Unverified