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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 3031–3040 of 3687 papers

Title	Date	Tasks	Status	Hype
A Multi-Task Learning Framework for Overcoming the Catastrophic Forgetting in Automatic Speech Recognition	Apr 17, 2019	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
Reinforcement Learning Based Emotional Editing Constraint Conversation Generation	Apr 17, 2019	Multi-Task Learningreinforcement-learning	—Unverified	0
MultiNet++: Multi-Stream Feature Aggregation and Geometric Loss Strategy for Multi-Task Learning	Apr 15, 2019	Autonomous DrivingMulti-Task Learning	—Unverified	0
Low-Rank Deep Convolutional Neural Network for Multi-Task Learning	Apr 12, 2019	AttributeMulti-Task Learning	—Unverified	0
Strong Baselines for Complex Word Identification across Multiple Languages	Apr 11, 2019	Complex Word IdentificationMulti-Task Learning	CodeCode Available	0
Context-Aware Embeddings for Automatic Art Analysis	Apr 10, 2019	Art AnalysisCross-Modal Retrieval	CodeCode Available	0
What and How Well You Performed? A Multitask Learning Approach to Action Quality Assessment	Apr 8, 2019	Action ClassificationAction Quality Assessment	CodeCode Available	1
AutoSeM: Automatic Task Selection and Mixing in Multi-Task Learning	Apr 8, 2019	Bayesian OptimizationInductive Bias	—Unverified	0
An Integrated Approach for Keyphrase Generation via Exploring the Power of Retrieval and Extraction	Apr 6, 2019	Keyphrase GenerationMulti-Task Learning	CodeCode Available	0
A Multi-task Learning Approach for Named Entity Recognition using Local Detection	Apr 5, 2019	Multi-Task Learningnamed-entity-recognition	—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