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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 631–640 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
Joint Acne Image Grading and Counting via Label Distribution Learning	Oct 1, 2019	Acne Severity GradingMedical Image Classification	CodeCode Available	0	5
It Takes Two Flints to Make a Fire: Multitask Learning of Neural Relation and Explanation Classifiers	Apr 25, 2022	Multi-Task LearningRelation	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
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
BCH-NLP at BioCreative VII Track 3: medications detection in tweets using transformer networks and multi-task learning	Nov 26, 2021	AllData Augmentation	CodeCode Available	0	5
Intrinsically Motivated Open-Ended Multi-Task Learning Using Transfer Learning to Discover Task Hierarchy	Feb 19, 2021	Active LearningHierarchical Reinforcement Learning	CodeCode Available	0	5
Adversarial Data Programming: Using GANs to Relax the Bottleneck of Curated Labeled Data	Mar 14, 2018	Multi-Task LearningTransfer Learning	CodeCode Available	0	5
Interpreting and Exploiting Functional Specialization in Multi-Head Attention under Multi-task Learning	Oct 16, 2023	Multi-Task LearningTransfer Learning	CodeCode Available	0	5
High-order Joint Constituency and Dependency Parsing	Sep 21, 2023	Dependency ParsingMulti-Task Learning	CodeCode Available	0	5
Bayesian Neural Networks With Maximum Mean Discrepancy Regularization	Mar 2, 2020	image-classificationImage Classification	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