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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 2501–2510 of 3687 papers

Title	Date	Tasks	Status	Hype
VRUNet: Multi-Task Learning Model for Intent Prediction of Vulnerable Road Users	Jul 10, 2020	Autonomous VehiclesMotion Planning	—Unverified	0
Neural Knowledge Extraction From Cloud Service Incidents	Jul 10, 2020	Cloud ComputingEntity Extraction using GAN	—Unverified	0
Deep Multi-task Learning for Facial Expression Recognition and Synthesis Based on Selective Feature Sharing	Jul 9, 2020	Facial Expression RecognitionFacial Expression Recognition (FER)	—Unverified	0
Simultaneous Estimation of X-ray Back-Scatter and Forward-Scatter using Multi-Task Learning	Jul 8, 2020	BlockingMulti-Task Learning	—Unverified	0
An encoder-decoder-based method for COVID-19 lung infection segmentation	Jul 2, 2020	DecoderMulti-Task Learning	—Unverified	0
A Brief Review of Deep Multi-task Learning and Auxiliary Task Learning	Jul 2, 2020	Multi-Task Learning	—Unverified	0
Learning to Segment from Scribbles using Multi-scale Adversarial Attention Gates	Jul 2, 2020	Deep AttentionImage Segmentation	CodeCode Available	1
The NTT DCASE2020 Challenge Task 6 system: Automated Audio Captioning with Keywords and Sentence Length Estimation	Jul 1, 2020	Audio captioningCaption Generation	—Unverified	0
Multi-Task Variational Information Bottleneck	Jul 1, 2020	Multi-Task Learningspeech-recognition	—Unverified	0
A BERT-based One-Pass Multi-Task Model for Clinical Temporal Relation Extraction	Jul 1, 2020	Multi-Task LearningRelation	—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