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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 1971–1980 of 3687 papers

Title	Date	Tasks	Status	Hype
Compositional Models: Multi-Task Learning and Knowledge Transfer with Modular Networks	Jul 23, 2021	Domain Adaptationimage-classification	—Unverified	0
Adaptive Transfer Learning on Graph Neural Networks	Jul 19, 2021	Meta-LearningMulti-Task Learning	CodeCode Available	1
RECIST-Net: Lesion detection via grouping keypoints on RECIST-based annotation	Jul 19, 2021	Computed Tomography (CT)Lesion Detection	—Unverified	0
TFix: Learning to Fix Coding Errors with a Text-to-Text Transformer	Jul 18, 2021	Code GenerationMulti-Task Learning	CodeCode Available	1
Proactive Retrieval-based Chatbots based on Relevant Knowledge and Goals	Jul 18, 2021	Multi-Task LearningRetrieval	CodeCode Available	1
Multiple Instance Learning with Auxiliary Task Weighting for Multiple Myeloma Classification	Jul 16, 2021	Multiple Instance LearningMulti-Task Learning	CodeCode Available	0
Multi-task Learning with Cross Attention for Keyword Spotting	Jul 15, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
Multi-Task Learning based Online Dialogic Instruction Detection with Pre-trained Language Models	Jul 15, 2021	Multi-Task Learning	CodeCode Available	0
MugRep: A Multi-Task Hierarchical Graph Representation Learning Framework for Real Estate Appraisal	Jul 12, 2021	Decision MakingGraph Representation Learning	—Unverified	0
Legal Judgment Prediction with Multi-Stage CaseRepresentation Learning in the Real Court Setting	Jul 12, 2021	Multi-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