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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 321–330 of 3687 papers

Title	Date	Tasks	Status	Hype
CodeFill: Multi-token Code Completion by Jointly Learning from Structure and Naming Sequences	Feb 14, 2022	Code CompletionLanguage Modelling	CodeCode Available	1
Auto-Lambda: Disentangling Dynamic Task Relationships	Feb 7, 2022	Auxiliary LearningMeta-Learning	CodeCode Available	1
Multi-task graph neural networks for simultaneous prediction of global and atomic properties in ferromagnetic systems	Feb 4, 2022	Multi-Task Learning	CodeCode Available	1
Molecular Representation Learning via Heterogeneous Motif Graph Neural Networks	Feb 1, 2022	graph constructionGraph Neural Network	CodeCode Available	1
Incorporating Commonsense Knowledge into Story Ending Generation via Heterogeneous Graph Networks	Jan 29, 2022	Multi-Task Learning	CodeCode Available	1
Global-Reasoned Multi-Task Learning Model for Surgical Scene Understanding	Jan 28, 2022	Graph AttentionKnowledge Distillation	CodeCode Available	1
MT-GBM: A Multi-Task Gradient Boosting Machine with Shared Decision Trees	Jan 17, 2022	Multi-Task Learning	CodeCode Available	1
Flexible Style Image Super-Resolution using Conditional Objective	Jan 13, 2022	Image Super-ResolutionMulti-Task Learning	CodeCode Available	1
Multi-task Joint Strategies of Self-supervised Representation Learning on Biomedical Networks for Drug Discovery	Jan 12, 2022	Drug DiscoveryGraph Attention	CodeCode Available	1
In Defense of the Unitary Scalarization for Deep Multi-Task Learning	Jan 11, 2022	Multi-Task LearningReinforcement Learning (RL)	CodeCode Available	1

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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