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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 771–780 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
Augmenting Biomedical Named Entity Recognition with General-domain Resources	Jun 15, 2024	Language ModellingMulti-Task Learning	CodeCode Available	0	5
A Syntax-aware Multi-task Learning Framework for Chinese Semantic Role Labeling	Nov 12, 2019	Chinese Semantic Role LabelingMulti-Task Learning	CodeCode Available	0	5
Data Fusion for Multi-Task Learning of Building Extraction and Height Estimation	Aug 5, 2023	Multi-Task Learning	CodeCode Available	0	5
Asynchronous Multi-Task Learning	Sep 30, 2016	Multi-Task LearningTransfer Learning	CodeCode Available	0	5
Improving End-to-End Text Image Translation From the Auxiliary Text Translation Task	Oct 8, 2022	Multi-Task LearningTranslation	CodeCode Available	0	5
LCT-1 at SemEval-2023 Task 10: Pre-training and Multi-task Learning for Sexism Detection and Classification	Jun 8, 2023	Domain AdaptationMulti-Task Learning	CodeCode Available	0	5
Deep Multi-Task Augmented Feature Learning via Hierarchical Graph Neural Network	Feb 12, 2020	Graph Neural NetworkMulti-Task Learning	CodeCode Available	0	5
Learned Weight Sharing for Deep Multi-Task Learning by Natural Evolution Strategy and Stochastic Gradient Descent	Mar 23, 2020	Multi-Task Learning	CodeCode Available	0	5
Data exploitation: multi-task learning of object detection and semantic segmentation on partially annotated data	Nov 7, 2023	Knowledge DistillationMulti-Task Learning	CodeCode Available	0	5
Imbalanced multi-label classification using multi-task learning with extractive summarization	Mar 16, 2019	ClassificationExtractive Summarization	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