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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 831–840 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
Improving Dialectal Slot and Intent Detection with Auxiliary Tasks: A Multi-Dialectal Bavarian Case Study	Jan 7, 2025	intent-classificationIntent Classification	CodeCode Available	0	5
Inductive biases of multi-task learning and finetuning: multiple regimes of feature reuse	Oct 3, 2023	feature selectionimage-classification	CodeCode Available	0	5
A Survey of Generative Information Retrieval	Jun 3, 2024	Information RetrievalMulti-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
Improved Abdominal Multi-Organ Segmentation via 3D Boundary-Constrained Deep Neural Networks	Oct 9, 2022	DecoderImage Segmentation	CodeCode Available	0	5
Image Aesthetic Assessment Assisted by Attributes through Adversarial Learning	Jan 1, 2019	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
Identification of Negative Transfers in Multitask Learning Using Surrogate Models	Mar 25, 2023	Multi-Task Learning	CodeCode Available	0	5
Identification of Distorted RF Components via Deep Multi-Task Learning	Jul 4, 2022	Multi-Task Learning	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

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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