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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 3031–3040 of 3687 papers

Title	Date	Tasks	Status	Hype
Label Hierarchy Transition: Delving into Class Hierarchies to Enhance Deep Classifiers	Dec 4, 2021	ClassificationMulti-class Classification	CodeCode Available	0
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
Data Fusion for Multi-Task Learning of Building Extraction and Height Estimation	Aug 5, 2023	Multi-Task Learning	CodeCode Available	0
To train or not to train adversarially: A study of bias mitigation strategies for speaker recognition	Mar 17, 2022	Face RecognitionFairness	CodeCode Available	0
Is POS Tagging Necessary or Even Helpful for Neural Dependency Parsing?	Mar 6, 2020	Dependency ParsingFeature Engineering	CodeCode Available	0
High-order Joint Constituency and Dependency Parsing	Sep 21, 2023	Dependency ParsingMulti-Task Learning	CodeCode Available	0
Touch the Core: Exploring Task Dependence Among Hybrid Targets for Recommendation	Mar 26, 2024	Multi-Task LearningRecommendation Systems	CodeCode Available	0
Cardiac Complication Risk Profiling for Cancer Survivors via Multi-View Multi-Task Learning	Sep 25, 2021	Multi-Task Learning	CodeCode Available	0
Read, Watch, and Move: Reinforcement Learning for Temporally Grounding Natural Language Descriptions in Videos	Jan 21, 2019	Decision MakingMulti-Task Learning	CodeCode Available	0
A Transformer Framework for Data Fusion and Multi-Task Learning in Smart Cities	Nov 18, 2022	Computational EfficiencyHumanitarian	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