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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 21–30 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
Relational Multi-Task Learning: Modeling Relations between Data and Tasks	Mar 14, 2023	Multi-Task LearningTransfer Learning	CodeCode Available	3	5
ERNIE 2.0: A Continual Pre-training Framework for Language Understanding	Jul 29, 2019	Chinese Named Entity RecognitionChinese Reading Comprehension	CodeCode Available	3	5
Ludwig: a type-based declarative deep learning toolbox	Sep 17, 2019	DecoderDeep Learning	CodeCode Available	3	5
Language Models are Few-Shot Learners	May 28, 2020	answerability predictionArticles	CodeCode Available	3	5
MixLoRA: Enhancing Large Language Models Fine-Tuning with LoRA-based Mixture of Experts	Apr 22, 2024	Common Sense ReasoningGPU	CodeCode Available	3	5
Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next	Jan 14, 2022	Multi-Task Learning	CodeCode Available	3	5
AdapterFusion: Non-Destructive Task Composition for Transfer Learning	May 1, 2020	Language ModellingMulti-Task Learning	CodeCode Available	2	5
Joint 2D-3D Multi-Task Learning on Cityscapes-3D: 3D Detection, Segmentation, and Depth Estimation	Apr 3, 2023	3D Object DetectionAutonomous Driving	CodeCode Available	2	5
In-BoXBART: Get Instructions into Biomedical Multi-Task Learning	Apr 15, 2022	Few-Shot LearningMulti-Task Learning	CodeCode Available	2	5
InvPT++: Inverted Pyramid Multi-Task Transformer for Visual Scene Understanding	Jun 8, 2023	DecoderMulti-Task Learning	CodeCode Available	2	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