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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 321–330 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
Forgetting to learn logic programs	Nov 15, 2019	Inductive logic programmingMulti-Task Learning	CodeCode Available	1	5
A Large Scale Search Dataset for Unbiased Learning to Rank	Jul 7, 2022	Causal DiscoveryLanguage Modelling	CodeCode Available	1	5
A Recurrent Vision-and-Language BERT for Navigation	Nov 26, 2020	Decision MakingDecoder	CodeCode Available	1	5
Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning	Jun 23, 2020	Knowledge GraphsMulti-Task Learning	CodeCode Available	1	5
Improvable Gap Balancing for Multi-Task Learning	Jul 28, 2023	Deep Reinforcement LearningMulti-Task Learning	CodeCode Available	1	5
Improved Feature Distillation via Projector Ensemble	Oct 27, 2022	Knowledge DistillationMulti-Task Learning	CodeCode Available	1	5
An End-to-End Multi-Task Learning Model for Image-based Table Recognition	Mar 15, 2023	Cell DetectionDecoder	CodeCode Available	1	5
Improving Neural Cross-Lingual Summarization via Employing Optimal Transport Distance for Knowledge Distillation	Dec 7, 2021	Knowledge DistillationMulti-Task Learning	CodeCode Available	1	5
A Frustratingly Easy Approach for Entity and Relation Extraction	Oct 24, 2020	Joint Entity and Relation ExtractionMulti-Task Learning	CodeCode Available	1	5
Audio-Visual Deception Detection: DOLOS Dataset and Parameter-Efficient Crossmodal Learning	Mar 9, 2023	Deception DetectionMulti-Task Learning	CodeCode Available	1	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