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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 1671–1680 of 3687 papers

Title	Date	Tasks	Status	Hype
Evidentiality-guided Generation for Knowledge-Intensive NLP Tasks	Jan 16, 2022	Fact VerificationMemorization	—Unverified	0
In Situ Answer Sentence Selection at Web-scale	Jan 16, 2022	Multi-Task LearningOpen-Domain Question Answering	—Unverified	0
Robust Scatterer Number Density Segmentation of Ultrasound Images	Jan 16, 2022	Domain AdaptationMulti-Task Learning	—Unverified	0
Self-Supervision and Multi-Task Learning: Challenges in Fine-Grained COVID-19 Multi-Class Classification from Chest X-rays	Jan 16, 2022	ClassificationMulti-class Classification	—Unverified	0
A Novel Multi-Task Learning Method for Symbolic Music Emotion Recognition	Jan 15, 2022	Emotion RecognitionLanguage Modeling	—Unverified	0
Multi-View representation learning in Multi-Task Scene	Jan 15, 2022	Multi-Task LearningMULTI-VIEW LEARNING	—Unverified	0
Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next	Jan 14, 2022	Multi-Task Learning	CodeCode Available	3
A Study of Transducer based End-to-End ASR with ESPnet: Architecture, Auxiliary Loss and Decoding Strategies	Jan 14, 2022	Multi-Task Learning	—Unverified	0
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

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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