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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 1861–1870 of 3687 papers

Title	Date	Tasks	Status	Hype
Consistency Training of Multi-exit Architectures for Sensor Data	Sep 27, 2021	Multi-Task Learning	—Unverified	0
Graph Reasoning with Context-Aware Linearization for Interpretable Fact Extraction and Verification	Sep 25, 2021	Graph AttentionMulti-Task Learning	—Unverified	0
Cardiac Complication Risk Profiling for Cancer Survivors via Multi-View Multi-Task Learning	Sep 25, 2021	Multi-Task Learning	CodeCode Available	0
Multi-task Learning with Domain Knowledge for Molecular Property Prediction	Sep 24, 2021	Drug DiscoveryMolecular Property Prediction	—Unverified	0
CSAGN: Conversational Structure Aware Graph Network for Conversational Semantic Role Labeling	Sep 23, 2021	Dialogue UnderstandingMulti-Task Learning	CodeCode Available	0
Improved optimization strategies for deep Multi-Task Networks	Sep 21, 2021	Computational EfficiencyMulti-Task Learning	—Unverified	0
Multi-Task Learning with Sentiment, Emotion, and Target Detection to Recognize Hate Speech and Offensive Language	Sep 21, 2021	Emotion RecognitionModel Selection	—Unverified	0
Comparison of single and multitask learning for predicting cognitive decline based on MRI data	Sep 21, 2021	DiagnosticDomain Adaptation	CodeCode Available	0
CUNI systems for WMT21: Multilingual Low-Resource Translation for Indo-European Languages Shared Task	Sep 20, 2021	Grapheme-to-Phoneme ConversionMulti-Task Learning	—Unverified	0
Lifelong Robotic Reinforcement Learning by Retaining Experiences	Sep 19, 2021	Multi-Task Learningreinforcement-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