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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 321–330 of 3687 papers

Title	Date	Tasks	Status	Hype
Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less Data	Sep 19, 2020	Multi-Task LearningNatural Language Inference	CodeCode Available	1
A Large Scale Search Dataset for Unbiased Learning to Rank	Jul 7, 2022	Causal DiscoveryLanguage Modelling	CodeCode Available	1
A Recurrent Vision-and-Language BERT for Navigation	Nov 26, 2020	Decision MakingDecoder	CodeCode Available	1
Federated Multi-Task Learning under a Mixture of Distributions	Aug 23, 2021	FairnessFederated Learning	CodeCode Available	1
A New Look and Convergence Rate of Federated Multi-Task Learning with Laplacian Regularization	Feb 14, 2021	Federated LearningFew-Shot Learning	CodeCode Available	1
Few-shot Knowledge Graph-to-Text Generation with Pretrained Language Models	Jun 3, 2021	KG-to-Text GenerationMulti-Task Learning	CodeCode Available	1
Customizing Language Models with Instance-wise LoRA for Sequential Recommendation	Aug 19, 2024	Mixture-of-ExpertsMulti-Task Learning	CodeCode Available	1
Florence-2: Advancing a Unified Representation for a Variety of Vision Tasks	Nov 10, 2023	DiversityMulti-Task Learning	CodeCode Available	1
End-to-end Autonomous Driving with Semantic Depth Cloud Mapping and Multi-agent	Apr 12, 2022	Autonomous DrivingMulti-Task Learning	CodeCode Available	1
An End-to-End Multi-Task Learning Model for Image-based Table Recognition	Mar 15, 2023	Cell DetectionDecoder	CodeCode Available	1

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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