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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 811–820 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
It Takes Two Flints to Make a Fire: Multitask Learning of Neural Relation and Explanation Classifiers	Apr 25, 2022	Multi-Task LearningRelation	CodeCode Available	0	5
Latent Variable Model for Multi-modal Translation	Nov 1, 2018	DecoderMachine Translation	CodeCode Available	0	5
DaN+: Danish Nested Named Entities and Lexical Normalization	May 24, 2021	Cross-Lingual TransferLexical Normalization	CodeCode Available	0	5
Image Captioning with Clause-Focused Metrics in a Multi-Modal Setting for Marketing	May 6, 2019	DescriptiveImage Captioning	CodeCode Available	0	5
Cyclic Guidance for Weakly Supervised Joint Detection and Segmentation	Jun 1, 2019	Image-level Supervised Instance SegmentationMulti-Task Learning	CodeCode Available	0	5
Image Aesthetic Assessment Assisted by Attributes through Adversarial Learning	Jan 1, 2019	Multi-Task Learning	CodeCode Available	0	5
De-identification of Privacy-related Entities in Job Postings	May 24, 2021	De-identificationMulti-Task Learning	CodeCode Available	0	5
Autocorrect in the Process of Translation -- Multi-task Learning Improves Dialogue Machine Translation	Mar 30, 2021	Machine TranslationMulti-Task Learning	CodeCode Available	0	5
Image Splicing Localization Using A Multi-Task Fully Convolutional Network (MFCN)	Sep 6, 2017	Multi-Task Learning	CodeCode Available	0	5
Identification of Negative Transfers in Multitask Learning Using Surrogate Models	Mar 25, 2023	Multi-Task Learning	CodeCode Available	0	5

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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