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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 211–220 of 3687 papers

Title	Date	Tasks	Status	Hype
Efficient Diffusion Training via Min-SNR Weighting Strategy	Mar 16, 2023	DenoisingImage Generation	CodeCode Available	1
An End-to-End Multi-Task Learning Model for Image-based Table Recognition	Mar 15, 2023	Cell DetectionDecoder	CodeCode Available	1
Predictive Experience Replay for Continual Visual Control and Forecasting	Mar 12, 2023	Continual LearningModel-based Reinforcement Learning	CodeCode Available	1
HiNet: Novel Multi-Scenario & Multi-Task Learning with Hierarchical Information Extraction	Mar 10, 2023	Multi-Task LearningRecommendation Systems	CodeCode Available	1
Audio-Visual Deception Detection: DOLOS Dataset and Parameter-Efficient Crossmodal Learning	Mar 9, 2023	Deception DetectionMulti-Task Learning	CodeCode Available	1
Searching for Effective Neural Network Architectures for Heart Murmur Detection from Phonocardiogram	Mar 6, 2023	Model SelectionMulti-Task Learning	CodeCode Available	1
Compressed Interaction Graph based Framework for Multi-behavior Recommendation	Mar 4, 2023	Multi-Task Learning	CodeCode Available	1
Image-Based and Partially Categorical Annotating Approach for Pedestrian Attribute Recognition	Feb 28, 2023	AttributeMulti-Task Learning	CodeCode Available	1
Gradient Remedy for Multi-Task Learning in End-to-End Noise-Robust Speech Recognition	Feb 22, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available	1
Recon: Reducing Conflicting Gradients from the Root for Multi-Task Learning	Feb 22, 2023	Multi-Task Learning	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