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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 911–920 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
HyperFace: A Deep Multi-task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition	Mar 3, 2016	Face DetectionMulti-Task Learning	CodeCode Available	0	5
Hybrid Losses for Hierarchical Embedding Learning	Jan 22, 2025	Multi-Task LearningRetrieval	CodeCode Available	0	5
Human Keypoint Detection by Progressive Context Refinement	Oct 27, 2019	Human DetectionKeypoint Detection	CodeCode Available	0	5
Multi-task Ensembles with Crowdsourced Features Improve Skin Lesion Diagnosis	Apr 28, 2020	DiagnosticMulti-Task Learning	CodeCode Available	0	5
HTR-JAND: Handwritten Text Recognition with Joint Attention Network and Knowledge Distillation	Dec 24, 2024	Computational EfficiencyHandwritten Text Recognition	CodeCode Available	0	5
Cross-Domain Self-supervised Multi-task Feature Learning using Synthetic Imagery	Nov 24, 2017	Domain AdaptationMulti-Task Learning	CodeCode Available	0	5
HRNet: Differentially Private Hierarchical and Multi-Resolution Network for Human Mobility Data Synthesization	May 13, 2024	Multi-Task Learning	CodeCode Available	0	5
Domain Aware Multi-Task Pretraining of 3D Swin Transformer for T1-weighted Brain MRI	Oct 1, 2024	AnatomyContrastive Learning	CodeCode Available	0	5
Hybrid Dual Mean-Teacher Network With Double-Uncertainty Guidance for Semi-Supervised Segmentation of MRI Scans	Mar 9, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available	0	5
Critical Learning Periods Emerge Even in Deep Linear Networks	Aug 23, 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