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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 2421–2430 of 3687 papers

Title	Date	Tasks	Status	Hype
Effects of Word-frequency based Pre- and Post- Processings for Audio Captioning	Sep 24, 2020	Audio captioningData Augmentation	—Unverified	0
Rank-Based Multi-task Learning for Fair Regression	Sep 23, 2020	FairnessMulti-Task Learning	—Unverified	0
Label-Efficient Multi-Task Segmentation using Contrastive Learning	Sep 23, 2020	Contrastive LearningMulti-Task Learning	CodeCode Available	1
Relation Extraction from Biomedical and Clinical Text: Unified Multitask Learning Framework	Sep 20, 2020	Multi-Task LearningRelation	—Unverified	0
Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less Data	Sep 19, 2020	Multi-Task LearningNatural Language Inference	CodeCode Available	1
Aggressive Language Detection with Joint Text Normalization via Adversarial Multi-task Learning	Sep 19, 2020	Multi-Task LearningText Normalization	—Unverified	0
An Interpretable and Uncertainty Aware Multi-Task Framework for Multi-Aspect Sentiment Analysis	Sep 18, 2020	Extract AspectMulti-Task Learning	CodeCode Available	0
Retrofitting Structure-aware Transformer Language Model for End Tasks	Sep 16, 2020	Language ModelingLanguage Modelling	—Unverified	0
Frequency-based Multi Task learning With Attention Mechanism for Fault Detection In Power Systems	Sep 15, 2020	Fault DetectionMulti-Task Learning	—Unverified	0
Knowledge Adaption for Demand Prediction based on Multi-task Memory Neural Network	Sep 12, 2020	Demand ForecastingMulti-Task Learning	—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