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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 1551–1560 of 3687 papers

Title	Date	Tasks	Status	Hype
Improving Few-Shot Part Segmentation using Coarse Supervision	Apr 11, 2022	Multi-Task LearningSegmentation	—Unverified	0
MIME: Adapting a Single Neural Network for Multi-task Inference with Memory-efficient Dynamic Pruning	Apr 11, 2022	Multi-Task Learning	—Unverified	0
Segmentation-Consistent Probabilistic Lesion Counting	Apr 11, 2022	Lesion SegmentationMulti-Task Learning	CodeCode Available	0
Efficient Extraction of Pathologies from C-Spine Radiology Reports using Multi-Task Learning	Apr 9, 2022	Multi-Task Learning	—Unverified	0
No Task Left Behind: Multi-Task Learning of Knowledge Tracing and Option Tracing for Better Student Assessment	Apr 8, 2022	Knowledge TracingMultiple-choice	—Unverified	0
Detecting Dysfluencies in Stuttering Therapy Using wav2vec 2.0	Apr 7, 2022	Multi-Task Learningspeech-recognition	—Unverified	0
MTI-Net: A Multi-Target Speech Intelligibility Prediction Model	Apr 7, 2022	Multi-Task LearningPrediction	—Unverified	0
A Survey of Multi-task Learning in Natural Language Processing: Regarding Task Relatedness and Training Methods	Apr 7, 2022	Multi-Task Learning	—Unverified	0
Multi-Task Distributed Learning using Vision Transformer with Random Patch Permutation	Apr 7, 2022	Federated LearningManagement	—Unverified	0
Hear No Evil: Towards Adversarial Robustness of Automatic Speech Recognition via Multi-Task Learning	Apr 5, 2022	Adversarial AttackAdversarial Robustness	—Unverified	0

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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