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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 1501–1510 of 3687 papers

Title	Date	Tasks	Status	Hype
Improving on-device speaker verification using federated learning with privacy	Aug 6, 2020	Federated LearningMulti-Task Learning	—Unverified	0
Improving out-of-distribution generalization via multi-task self-supervised pretraining	Mar 30, 2020	Adversarial RobustnessDomain Generalization	—Unverified	0
FineText: Text Classification via Attention-based Language Model Fine-tuning	Oct 25, 2019	BenchmarkingClassification	—Unverified	0
Improving Perceptual Quality, Intelligibility, and Acoustics on VoIP Platforms	Mar 16, 2023	Multi-Task LearningSpeech Enhancement	—Unverified	0
Improving Prediction of Low-Prior Clinical Events with Simultaneous General Patient-State Representation Learning	Jun 28, 2021	Multi-Task LearningPrediction	—Unverified	0
Improving Prosody for Unseen Texts in Speech Synthesis by Utilizing Linguistic Information and Noisy Data	Nov 15, 2021	Chinese Word SegmentationMulti-Task Learning	—Unverified	0
Comprehensive Video Understanding: Video summarization with content-based video recommender design	Oct 30, 2019	Action RecognitionData Augmentation	—Unverified	0
Improving Robotic Grasping on Monocular Images Via Multi-Task Learning and Positional Loss	Nov 5, 2020	Multi-Task LearningRobotic Grasping	—Unverified	0
Deep Estimation of Speckle Statistics Parametric Images	Jun 8, 2022	Multi-Task Learning	—Unverified	0
Compositional Zero-Shot Domain Transfer with Text-to-Text Models	Mar 23, 2023	Data AugmentationMulti-Task Learning	—Unverified	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