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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 501–510 of 3687 papers

Title	Date	Tasks	Status	Hype
Robust Learning Through Cross-Task Consistency	Jun 7, 2020	3D ReconstructionDepth Estimation	CodeCode Available	1
An Efficient Framework for Clustered Federated Learning	Jun 7, 2020	ClusteringFederated Learning	CodeCode Available	1
Encoding formulas as deep networks: Reinforcement learning for zero-shot execution of LTL formulas	Jun 1, 2020	MinecraftMulti-Task Learning	CodeCode Available	1
Massive Choice, Ample Tasks (MaChAmp): A Toolkit for Multi-task Learning in NLP	May 29, 2020	Dependency ParsingLanguage Modeling	CodeCode Available	1
Deep Learning for Automatic Pneumonia Detection	May 28, 2020	Deep LearningDiagnostic	CodeCode Available	1
M2GRL: A Multi-task Multi-view Graph Representation Learning Framework for Web-scale Recommender Systems	May 20, 2020	Graph Representation LearningInductive Bias	CodeCode Available	1
An Empirical Study of Multi-Task Learning on BERT for Biomedical Text Mining	May 6, 2020	Multi-Task Learningnamed-entity-recognition	CodeCode Available	1
Multi-task pre-training of deep neural networks for digital pathology	May 5, 2020	General ClassificationMulti-Task Learning	CodeCode Available	1
Words aren't enough, their order matters: On the Robustness of Grounding Visual Referring Expressions	May 4, 2020	Contrastive LearningMulti-Task Learning	CodeCode Available	1
PAMTRI: Pose-Aware Multi-Task Learning for Vehicle Re-Identification Using Highly Randomized Synthetic Data	May 2, 2020	AttributeMulti-Task Learning	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