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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 1271–1280 of 3687 papers

Title	Date	Tasks	Status	Hype
Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models	Oct 18, 2022	image-classificationImage Classification	CodeCode Available	1
Understanding COVID-19 Vaccine Campaign on Facebook using Minimal Supervision	Oct 18, 2022	Multi-Task Learning	CodeCode Available	0
When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework and A New Benchmark	Oct 17, 2022	Age-Invariant Face RecognitionFace Generation	—Unverified	0
PACIFIC: Towards Proactive Conversational Question Answering over Tabular and Textual Data in Finance	Oct 17, 2022	Code GenerationConversational Question Answering	CodeCode Available	1
Watermarking Pre-trained Language Models with Backdooring	Oct 14, 2022	Multi-Task Learning	—Unverified	0
Multi-Task Learning based Video Anomaly Detection with Attention	Oct 14, 2022	Anomaly DetectionMulti-Task Learning	—Unverified	0
Multi-Task Learning for Joint Semantic Role and Proto-Role Labeling	Oct 13, 2022	Multi-Task LearningSentence	—Unverified	0
Can Demographic Factors Improve Text Classification? Revisiting Demographic Adaptation in the Age of Transformers	Oct 13, 2022	Language ModelingLanguage Modelling	CodeCode Available	0
Prompt-based Connective Prediction Method for Fine-grained Implicit Discourse Relation Recognition	Oct 13, 2022	Multi-Task LearningRelation	CodeCode Available	0
Composite Learning for Robust and Effective Dense Predictions	Oct 13, 2022	Boundary DetectionDepth Estimation	—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