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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 1021–1030 of 3687 papers

Title	Date	Tasks	Status	Hype
Helping Visually Impaired People Take Better Quality Pictures	May 14, 2023	Multi-Task Learning	CodeCode Available	0
MetaMorphosis: Task-oriented Privacy Cognizant Feature Generation for Multi-task Learning	May 13, 2023	Deep LearningDepth Estimation	—Unverified	0
MTLSegFormer: Multi-task Learning with Transformers for Semantic Segmentation in Precision Agriculture	May 4, 2023	Multi-Task LearningSemantic Segmentation	—Unverified	0
Zenseact Open Dataset: A large-scale and diverse multimodal dataset for autonomous driving	May 3, 2023	Autonomous DrivingDiversity	CodeCode Available	1
Leveraging Language Representation for Material Recommendation, Ranking, and Exploration	May 1, 2023	Multi-Task Learning	CodeCode Available	1
Joint tone mapping and denoising of thermal infrared images via multi-scale Retinex and multi-task learning	May 1, 2023	DenoisingMulti-Task Learning	—Unverified	0
Multi-Task Structural Learning using Local Task Similarity induced Neuron Creation and Removal	Apr 30, 2023	Multi-Task Learning	CodeCode Available	0
MTC: A Multi-Task Model for Encrypted Network Traffic Classification Based on Transformer and 1D-CNN	Apr 29, 2023	Multi-Task LearningTraffic Classification	CodeCode Available	1
An Extensible Multimodal Multi-task Object Dataset with Materials	Apr 29, 2023	AttributeMulti-Task Learning	—Unverified	0
Ensemble Modeling with Contrastive Knowledge Distillation for Sequential Recommendation	Apr 28, 2023	AttributeContrastive Learning	CodeCode Available	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