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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 2241–2250 of 3687 papers

Title	Date	Tasks	Status	Hype
Encoding Syntactic Knowledge in Transformer Encoder for Intent Detection and Slot Filling	Dec 21, 2020	Intent DetectionMulti-Task Learning	—Unverified	0
Leveraging Meta-path Contexts for Classification in Heterogeneous Information Networks	Dec 18, 2020	ClassificationGeneral Classification	—Unverified	0
Exploiting Learnable Joint Groups for Hand Pose Estimation	Dec 17, 2020	Hand Pose EstimationMulti-Task Learning	CodeCode Available	1
MIX : a Multi-task Learning Approach to Solve Open-Domain Question Answering	Dec 17, 2020	Computational EfficiencyMulti-Task Learning	—Unverified	0
Task Uncertainty Loss Reduce Negative Transfer in Asymmetric Multi-task Feature Learning	Dec 17, 2020	Multi-Task Learning	—Unverified	0
Real-time Multi-Task Diffractive Deep Neural Networks via Hardware-Software Co-design	Dec 16, 2020	Multi-Task Learning	—Unverified	0
Towards Recognizing New Semantic Concepts in New Visual Domains	Dec 16, 2020	Domain AdaptationDomain Generalization	CodeCode Available	1
LiteMuL: A Lightweight On-Device Sequence Tagger using Multi-task Learning	Dec 15, 2020	Multi-Task LearningNER	—Unverified	0
Invariant Feature Learning for Sensor-based Human Activity Recognition	Dec 14, 2020	Activity RecognitionHuman Activity Recognition	—Unverified	0
Reasoning in Dialog: Improving Response Generation by Context Reading Comprehension	Dec 14, 2020	Multi-Task LearningReading Comprehension	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