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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 1251–1260 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
Graph-based Knowledge Distillation by Multi-head Attention Network	Jul 4, 2019	Inductive BiasKnowledge Distillation	CodeCode Available	0	5
Graph Neural Networks for Surfactant Multi-Property Prediction	Jan 3, 2024	Ensemble LearningMulti-Task Learning	CodeCode Available	0	5
Context-aware Multi-task Learning for Pedestrian Intent and Trajectory Prediction	Jul 24, 2024	Autonomous VehiclesMulti-Task Learning	CodeCode Available	0	5
GradCraft: Elevating Multi-task Recommendations through Holistic Gradient Crafting	Jul 29, 2024	Multi-Task LearningRecommendation Systems	CodeCode Available	0	5
Graph Star Net for Generalized Multi-Task Learning	Jun 21, 2019	ClassificationGeneral Classification	CodeCode Available	0	5
Happy Are Those Who Grade without Seeing: A Multi-Task Learning Approach to Grade Essays Using Gaze Behaviour	May 25, 2020	Multi-Task LearningNamed Entity Recognition (NER)	CodeCode Available	0	5
An Efficient End-to-End Approach to Noise Invariant Speech Features via Multi-Task Learning	Mar 13, 2024	DenoisingKnowledge Distillation	CodeCode Available	0	5
End-to-end Multi-Modal Multi-Task Vehicle Control for Self-Driving Cars with Visual Perception	Jan 20, 2018	Autonomous DrivingMulti-Task Learning	CodeCode Available	0	5
Generalized Block-Diagonal Structure Pursuit: Learning Soft Latent Task Assignment against Negative Transfer	Dec 1, 2019	AttributeMulti-Task Learning	CodeCode Available	0	5
Can Demographic Factors Improve Text Classification? Revisiting Demographic Adaptation in the Age of Transformers	Oct 13, 2022	Language ModelingLanguage Modelling	CodeCode Available	0	5

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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