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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 451–460 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
FINER: Enhancing State-of-the-art Classifiers with Feature Attribution to Facilitate Security Analysis	Aug 10, 2023	Malware AnalysisMulti-Task Learning	CodeCode Available	1	5
Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning	Feb 6, 2024	Bayesian InferenceMulti-Task Learning	CodeCode Available	1	5
Pre-training for Speech Translation: CTC Meets Optimal Transport	Jan 27, 2023	Multi-Task LearningSpeech-to-Text	CodeCode Available	1	5
Proactive Retrieval-based Chatbots based on Relevant Knowledge and Goals	Jul 18, 2021	Multi-Task LearningRetrieval	CodeCode Available	1	5
Hierarchical Multi-Label Classification of Scientific Documents	Nov 5, 2022	ClassificationHierarchical Multi-label Classification	CodeCode Available	1	5
Flexible Style Image Super-Resolution using Conditional Objective	Jan 13, 2022	Image Super-ResolutionMulti-Task Learning	CodeCode Available	1	5
Florence-2: Advancing a Unified Representation for a Variety of Vision Tasks	Nov 10, 2023	DiversityMulti-Task Learning	CodeCode Available	1	5
Question Answering over Electronic Devices: A New Benchmark Dataset and a Multi-Task Learning based QA Framework	Sep 13, 2021	Community Question AnsweringMulti-Task Learning	CodeCode Available	1	5
Forgetting to learn logic programs	Nov 15, 2019	Inductive logic programmingMulti-Task Learning	CodeCode Available	1	5
HiNet: Novel Multi-Scenario & Multi-Task Learning with Hierarchical Information Extraction	Mar 10, 2023	Multi-Task LearningRecommendation Systems	CodeCode Available	1	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