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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 921–930 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
Do Text-to-Text Multi-Task Learners Suffer from Task Conflict?	Dec 13, 2022	DecoderLanguage Modeling	CodeCode Available	0	5
Multi-Task Semantic Dependency Parsing with Policy Gradient for Learning Easy-First Strategies	Jun 4, 2019	Dependency ParsingMulti-Task Learning	CodeCode Available	0	5
Better, Faster, Stronger Sequence Tagging Constituent Parsers	Feb 28, 2019	Multi-Task LearningSentence	CodeCode Available	0	5
DRAGNN: A Transition-based Framework for Dynamically Connected Neural Networks	Mar 13, 2017	DecoderDependency Parsing	CodeCode Available	0	5
Multi-View Imputation and Cross-Attention Network Based on Incomplete Longitudinal and Multimodal Data for Conversion Prediction of Mild Cognitive Impairment	Jun 16, 2022	Disease PredictionImputation	CodeCode Available	0	5
DROP: Decouple Re-Identification and Human Parsing with Task-specific Features for Occluded Person Re-identification	Jan 31, 2024	Human ParsingMulti-Task Learning	CodeCode Available	0	5
HTR-JAND: Handwritten Text Recognition with Joint Attention Network and Knowledge Distillation	Dec 24, 2024	Computational EfficiencyHandwritten Text Recognition	CodeCode Available	0	5
Critical Learning Periods Emerge Even in Deep Linear Networks	Aug 23, 2023	Multi-Task Learning	CodeCode Available	0	5
Human Keypoint Detection by Progressive Context Refinement	Oct 27, 2019	Human DetectionKeypoint Detection	CodeCode Available	0	5
CPMR: Context-Aware Incremental Sequential Recommendation with Pseudo-Multi-Task Learning	Sep 9, 2023	Multi-Task LearningRecommendation Systems	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