SOTAVerified|Agents Browse Leaderboard About Blog

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 2371–2380 of 3687 papers

Title	Date	Tasks	Status	Hype
UserBERT: Self-supervised User Representation Learning	Jan 1, 2021	Multi-Task LearningRepresentation Learning	—Unverified	0
Variational Multi-Task Learning	Jan 1, 2021	Bayesian InferenceInductive Bias	—Unverified	0
Gated Ensemble of Spatio-temporal Mixture of Experts for Multi-task Learning in Ride-hailing System	Dec 31, 2020	Mixture-of-ExpertsMulti-Task Learning	—Unverified	0
Joint Air Quality and Weather Prediction Based on Multi-Adversarial Spatiotemporal Networks	Dec 30, 2020	Graph LearningGraph Neural Network	—Unverified	0
Enhancing Handwritten Text Recognition with N-gram sequence decomposition and Multitask Learning	Dec 28, 2020	Handwritten Text RecognitionLanguage Modelling	—Unverified	0
A multi-task learning network using shared BERT models for aspect-based sentiment analysis	Dec 27, 2020	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	—Unverified	0
Spatio-temporal Multi-task Learning for Cardiac MRI Left Ventricle Quantification	Dec 24, 2020	Model OptimizationMulti-Task Learning	CodeCode Available	0
Encoding Syntactic Knowledge in Transformer Encoder for Intent Detection and Slot Filling	Dec 21, 2020	Intent DetectionMulti-Task Learning	—Unverified	0
Leveraging Meta-path Contexts for Classification in Heterogeneous Information Networks	Dec 18, 2020	ClassificationGeneral Classification	—Unverified	0
MIX : a Multi-task Learning Approach to Solve Open-Domain Question Answering	Dec 17, 2020	Computational EfficiencyMulti-Task Learning	—Unverified	0

Show:10 25 50

← PrevPage 238 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