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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 931–940 of 3687 papers

Title	Date	Tasks	Status	Hype
Mitigating Negative Transfer with Task Awareness for Sexism, Hate Speech, and Toxic Language Detection	Jul 7, 2023	Multi-Task Learning	CodeCode Available	0
TBGC: Task-level Backbone-Oriented Gradient Clip for Multi-Task Foundation Model Learning	Jul 7, 2023	Data AugmentationMulti-Task Learning	—Unverified	0
Multi-Task Learning with Summary Statistics	Jul 5, 2023	Genetic Risk PredictionMulti-Task Learning	—Unverified	0
Multi-Task Learning to Enhance Generalizability of Neural Network Equalizers in Coherent Optical Systems	Jul 4, 2023	Multi-Task Learning	—Unverified	0
Multi-Task Learning Improves Performance In Deep Argument Mining Models	Jul 3, 2023	Argument MiningMulti-Task Learning	—Unverified	0
Towards Suicide Prevention from Bipolar Disorder with Temporal Symptom-Aware Multitask Learning	Jul 3, 2023	Multi-Task Learning	CodeCode Available	0
A region and category confidence-based multi-task network for carotid ultrasound image segmentation and classification	Jul 2, 2023	ClassificationImage Segmentation	—Unverified	0
Correct Like Humans: Progressive Learning Framework for Chinese Text Error Correction	Jun 30, 2023	Multi-Task Learning	—Unverified	0
FedBone: Towards Large-Scale Federated Multi-Task Learning	Jun 30, 2023	Federated LearningMulti-Task Learning	—Unverified	0
Feature Representation Learning for NL2SQL Generation Based on Coupling and Decoupling	Jun 30, 2023	Feature CorrelationMulti-Task Learning	—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