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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 781–790 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled Data	Mar 1, 2019	DenoisingGrammatical Error Correction	CodeCode Available	0	5
Learning Gating ConvNet for Two-Stream based Methods in Action Recognition	Sep 12, 2017	Action ClassificationAction Recognition	CodeCode Available	0	5
Data exploitation: multi-task learning of object detection and semantic segmentation on partially annotated data	Nov 7, 2023	Knowledge DistillationMulti-Task Learning	CodeCode Available	0	5
Improved Abdominal Multi-Organ Segmentation via 3D Boundary-Constrained Deep Neural Networks	Oct 9, 2022	DecoderImage Segmentation	CodeCode Available	0	5
A Unified Framework for Generalizable Style Transfer: Style and Content Separation	Jun 13, 2018	DecoderMulti-Task Learning	CodeCode Available	0	5
Learning Relatedness between Types with Prototypes for Relation Extraction	Apr 1, 2021	Multi-Task LearningRelation	CodeCode Available	0	5
Imbalanced multi-label classification using multi-task learning with extractive summarization	Mar 16, 2019	ClassificationExtractive Summarization	CodeCode Available	0	5
Multi-task Learning and Catastrophic Forgetting in Continual Reinforcement Learning	Sep 22, 2019	Continual LearningDeep Reinforcement Learning	CodeCode Available	0	5
Inductive biases of multi-task learning and finetuning: multiple regimes of feature reuse	Oct 3, 2023	feature selectionimage-classification	CodeCode Available	0	5
A Survey on Multi-Task Learning	Jul 25, 2017	Active LearningClustering	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