SOTAVerified|Agents Browse Leaderboard About

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 1471–1480 of 3687 papers

Title	Date	Tasks	Status	Hype
Compressed Hierarchical Representations for Multi-Task Learning and Task Clustering	May 31, 2022	ClusteringMulti-Task Learning	CodeCode Available	0
Tackling Multiple Tasks with One Single Learning Framework	May 29, 2022	Multi-Task Learning	—Unverified	0
Automatic Expert Selection for Multi-Scenario and Multi-Task Search	May 28, 2022	Mixture-of-ExpertsMulti-Task Learning	—Unverified	0
Multi-Task Learning with Multi-Query Transformer for Dense Prediction	May 28, 2022	DecoderMulti-Task Learning	CodeCode Available	1
Task-Agnostic Continual Reinforcement Learning: Gaining Insights and Overcoming Challenges	May 28, 2022	Continual LearningContinuous Control	CodeCode Available	1
Selective Inference for Sparse Multitask Regression with Applications in Neuroimaging	May 27, 2022	Multi-Task Learningregression	—Unverified	0
Acoustic-to-articulatory Speech Inversion with Multi-task Learning	May 27, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
Cascading Residual Graph Convolutional Network for Multi-Behavior Recommendation	May 26, 2022	Multi-Task Learning	CodeCode Available	1
Eliciting and Understanding Cross-Task Skills with Task-Level Mixture-of-Experts	May 25, 2022	Mixture-of-ExpertsMulti-Task Learning	CodeCode Available	0
Primitive3D: 3D Object Dataset Synthesis from Randomly Assembled Primitives	May 25, 2022	3D Object ClassificationDataset Distillation	—Unverified	0

Show:10 25 50

← PrevPage 148 of 369Next →

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