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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 451–460 of 3687 papers

Title	Date	Tasks	Status	Hype
Ditto: Fair and Robust Federated Learning Through Personalization	Dec 8, 2020	FairnessFederated Learning	CodeCode Available	1
EXTENDING CONDITIONAL CONVOLUTION STRUCTURES FOR ENHANCING MULTITASKING CONTINUAL LEARNING	Dec 7, 2020	Computational EfficiencyContinual Learning	CodeCode Available	1
Detecting 32 Pedestrian Attributes for Autonomous Vehicles	Dec 4, 2020	AttributeAutonomous Driving	CodeCode Available	1
Learning Class-Transductive Intent Representations for Zero-shot Intent Detection	Dec 3, 2020	Intent DetectionMulti-Task Learning	CodeCode Available	1
Learning Spatial Attention for Face Super-Resolution	Dec 2, 2020	Face ParsingImage Super-Resolution	CodeCode Available	1
Multi-Task Learning for Knowledge Graph Completion with Pre-trained Language Models	Dec 1, 2020	Knowledge Graph CompletionKnowledge Graphs	CodeCode Available	1
Automatic Charge Identification from Facts: A Few Sentence-Level Charge Annotations is All You Need	Dec 1, 2020	AllMulti-Task Learning	CodeCode Available	1
TableGPT: Few-shot Table-to-Text Generation with Table Structure Reconstruction and Content Matching	Dec 1, 2020	Few-Shot LearningLanguage Modeling	CodeCode Available	1
Kungfupanda at SemEval-2020 Task 12: BERT-Based Multi-TaskLearning for Offensive Language Detection	Dec 1, 2020	Language ModelingLanguage Modelling	CodeCode Available	1
A Recurrent Vision-and-Language BERT for Navigation	Nov 26, 2020	Decision MakingDecoder	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