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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 1321–1330 of 3687 papers

Title	Date	Tasks	Status	Hype
Grape Cold Hardiness Prediction via Multi-Task Learning	Sep 21, 2022	Multi-Task LearningPrediction	—Unverified	0
Extreme Multi-Domain, Multi-Task Learning With Unified Text-to-Text Transfer Transformers	Sep 21, 2022	Code SummarizationMulti-Task Learning	CodeCode Available	0
Effective Adaptation in Multi-Task Co-Training for Unified Autonomous Driving	Sep 19, 2022	Autonomous DrivingMulti-Task Learning	—Unverified	0
Will It Blend? Mixing Training Paradigms & Prompting for Argument Quality Prediction	Sep 19, 2022	Argument MiningContrastive Learning	—Unverified	0
Detecting Political Biases of Named Entities and Hashtags on Twitter	Sep 16, 2022	Multi-Task LearningTask 2	CodeCode Available	0
Integrating Form and Meaning: A Multi-Task Learning Model for Acoustic Word Embeddings	Sep 14, 2022	FormMulti-Task Learning	CodeCode Available	0
MLT-LE: predicting drug-target binding affinity with multi-task residual neural networks	Sep 13, 2022	Drug DiscoveryMulti-Task Learning	CodeCode Available	0
Joint Alignment of Multi-Task Feature and Label Spaces for Emotion Cause Pair Extraction	Sep 9, 2022	Emotion-Cause Pair ExtractionMulti-Task Learning	CodeCode Available	0
A Multi-Task Learning Model for Super Resolution of Wireless Channel Characteristics	Sep 9, 2022	Multi-Task LearningSuper-Resolution	—Unverified	0
Multi-grained Label Refinement Network with Dependency Structures for Joint Intent Detection and Slot Filling	Sep 9, 2022	Graph AttentionIntent Detection	CodeCode Available	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