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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 1581–1590 of 3687 papers

Title	Date	Tasks	Status	Hype
Reinforcement Guided Multi-Task Learning Framework for Low-Resource Stereotype Detection	Mar 27, 2022	DiagnosticHate Speech Detection	CodeCode Available	0
FedGradNorm: Personalized Federated Gradient-Normalized Multi-Task Learning	Mar 24, 2022	Federated LearningMulti-Task Learning	—Unverified	0
Multitask Emotion Recognition Model with Knowledge Distillation and Task Discriminator	Mar 24, 2022	Emotion RecognitionKnowledge Distillation	—Unverified	0
Transformer-based Multimodal Information Fusion for Facial Expression Analysis	Mar 23, 2022	Action Unit DetectionArousal Estimation	—Unverified	0
A Computational Approach to Understand Mental Health from Reddit: Knowledge-aware Multitask Learning Framework	Mar 22, 2022	Multi-Task LearningTransfer Learning	—Unverified	0
Utterance Rewriting with Contrastive Learning in Multi-turn Dialogue	Mar 22, 2022	Contrastive LearningMulti-Task Learning	—Unverified	0
PersFormer: 3D Lane Detection via Perspective Transformer and the OpenLane Benchmark	Mar 21, 2022	3D Lane DetectionAutonomous Driving	CodeCode Available	2
Reflective Fiber Faults Detection and Characterization Using Long-Short-Term Memory	Mar 19, 2022	Fault DiagnosisMulti-Task Learning	—Unverified	0
To train or not to train adversarially: A study of bias mitigation strategies for speaker recognition	Mar 17, 2022	Face RecognitionFairness	CodeCode Available	0
DeepAD: A Robust Deep Learning Model of Alzheimer's Disease Progression for Real-World Clinical Applications	Mar 17, 2022	Multi-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