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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 591–600 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
Restoring Images with Unknown Degradation Factors by Recurrent Use of a Multi-branch Network	Jul 10, 2019	DeblurringImage Restoration	CodeCode Available	0	5
Boundary-aware Context Neural Network for Medical Image Segmentation	May 3, 2020	Image SegmentationMedical Image Segmentation	CodeCode Available	0	5
Adversarial Training for Code Retrieval with Question-Description Relevance Regularization	Oct 19, 2020	Multi-Task LearningRetrieval	CodeCode Available	0	5
Joint Learning of Saliency Detection and Weakly Supervised Semantic Segmentation	Sep 9, 2019	Multi-Task LearningSaliency Detection	CodeCode Available	0	5
Joint Acne Image Grading and Counting via Label Distribution Learning	Oct 1, 2019	Acne Severity GradingMedical Image Classification	CodeCode Available	0	5
Joint Alignment of Multi-Task Feature and Label Spaces for Emotion Cause Pair Extraction	Sep 9, 2022	Emotion-Cause Pair ExtractionMulti-Task Learning	CodeCode Available	0	5
Adversarial Robustness in Multi-Task Learning: Promises and Illusions	Oct 26, 2021	Adversarial RobustnessMulti-Task Learning	CodeCode Available	0	5
Joint CTC-Attention based End-to-End Speech Recognition using Multi-task Learning	Sep 21, 2016	DecoderMulti-Task Learning	CodeCode Available	0	5
Beyond task success: A closer look at jointly learning to see, ask, and GuessWhat	Sep 10, 2018	Multi-Task LearningReinforcement Learning	CodeCode Available	0	5
High-order Joint Constituency and Dependency Parsing	Sep 21, 2023	Dependency ParsingMulti-Task Learning	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