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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 411–420 of 3687 papers

Title	Date	Tasks	Status	Hype
Adversarial Multi-task Learning Enhanced Physics-informed Neural Networks for Solving Partial Differential Equations	Apr 29, 2021	Multi-Task Learning	CodeCode Available	1
T2NER: Transformers based Transfer Learning Framework for Named Entity Recognition	Apr 23, 2021	Domain AdaptationMulti-Task Learning	CodeCode Available	1
A Multi-Task Deep Learning Framework for Building Footprint Segmentation	Apr 19, 2021	Boundary DetectionDeep Learning	CodeCode Available	1
Graph-based Person Signature for Person Re-Identifications	Apr 14, 2021	AttributeMulti-Task Learning	CodeCode Available	1
ZS-BERT: Towards Zero-Shot Relation Extraction with Attribute Representation Learning	Apr 10, 2021	AttributeMulti-Task Learning	CodeCode Available	1
CodeTrans: Towards Cracking the Language of Silicon's Code Through Self-Supervised Deep Learning and High Performance Computing	Apr 6, 2021	API Sequence RecommendationCode Comment Generation	CodeCode Available	1
Annotating Columns with Pre-trained Language Models	Apr 5, 2021	Columns Property AnnotationColumn Type Annotation	CodeCode Available	1
Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representations	Apr 4, 2021	3D ReconstructionMulti-Task Learning	CodeCode Available	1
An Empirical Study on Channel Effects for Synthetic Voice Spoofing Countermeasure Systems	Apr 3, 2021	Data AugmentationMulti-Task Learning	CodeCode Available	1
Target Speaker Verification with Selective Auditory Attention for Single and Multi-talker Speech	Mar 30, 2021	Multi-Task LearningSpeaker Verification	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