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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 3431–3440 of 3687 papers

Title	Date	Tasks	Status	Hype
CNN-based Cascaded Multi-task Learning of High-level Prior and Density Estimation for Crowd Counting	Jul 30, 2017	Crowd CountingDensity Estimation	CodeCode Available	0
CnGAN: Generative Adversarial Networks for Cross-network user preference generation for non-overlapped users	Aug 25, 2020	DiversityMulti-Task Learning	CodeCode Available	0
Autocorrect in the Process of Translation -- Multi-task Learning Improves Dialogue Machine Translation	Mar 30, 2021	Machine TranslationMulti-Task Learning	CodeCode Available	0
Forecasting Early with Meta Learning	Jul 19, 2023	Meta-LearningMulti-Task Learning	CodeCode Available	0
MTLTS: A Multi-Task Framework To Obtain Trustworthy Summaries From Crisis-Related Microblogs	Dec 10, 2021	Multi-Task LearningRumour Detection	CodeCode Available	0
Self-Supervised Generalisation with Meta Auxiliary Learning	Jan 25, 2019	Auxiliary LearningMeta-Learning	CodeCode Available	0
Synergistic Learning with Multi-Task DeepONet for Efficient PDE Problem Solving	Aug 5, 2024	Geometry-based operator learningMulti-Task Learning	CodeCode Available	0
MTRec: Multi-Task Learning over BERT for News Recommendation	May 1, 2022	Multi-Task LearningNews Recommendation	CodeCode Available	0
A Unified Query-based Paradigm for Camouflaged Instance Segmentation	Aug 14, 2023	Boundary DetectionDecoder	CodeCode Available	0
Adversarial Multi-task Learning for End-to-end Metaphor Detection	May 26, 2023	Multi-Task LearningWord Sense Disambiguation	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