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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 851–860 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
Image Splicing Localization Using A Multi-Task Fully Convolutional Network (MFCN)	Sep 6, 2017	Multi-Task Learning	CodeCode Available	0	5
Improved Abdominal Multi-Organ Segmentation via 3D Boundary-Constrained Deep Neural Networks	Oct 9, 2022	DecoderImage Segmentation	CodeCode Available	0	5
MPF-GAN: an enhanced architecture for 3D face reconstruction	Oct 10, 2024	3D Face Reconstruction3D Reconstruction	CodeCode Available	0	5
Identifying beneficial task relations for multi-task learning in deep neural networks	Feb 27, 2017	Multi-Task Learning	CodeCode Available	0	5
IITK at SemEval-2024 Task 4: Hierarchical Embeddings for Detection of Persuasion Techniques in Memes	Apr 6, 2024	Binary ClassificationClassification	CodeCode Available	0	5
Curbing Task Interference using Representation Similarity-Guided Multi-Task Feature Sharing	Aug 19, 2022	Computational EfficiencyDecoder	CodeCode Available	0	5
Accurate Bundle Matching and Generation via Multitask Learning with Partially Shared Parameters	Oct 19, 2022	Multi-Task Learning	CodeCode Available	0	5
Identification of Negative Transfers in Multitask Learning Using Surrogate Models	Mar 25, 2023	Multi-Task Learning	CodeCode Available	0	5
Image Aesthetic Assessment Assisted by Attributes through Adversarial Learning	Jan 1, 2019	Multi-Task Learning	CodeCode Available	0	5
Improving Neural Story Generation by Targeted Common Sense Grounding	Aug 26, 2019	Common Sense ReasoningMulti-Task Learning	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