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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 1201–1210 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
Learning to Make Predictions on Graphs with Autoencoders	Feb 23, 2018	ClassificationGeneral Classification	CodeCode Available	0	5
Fine-Grained Emotion Prediction by Modeling Emotion Definitions	Jul 26, 2021	Language ModelingLanguage Modelling	CodeCode Available	0	5
Fine-grained Urban Flow Inference with Incomplete Data	Mar 1, 2022	Fine-Grained Urban Flow InferenceMulti-Task Learning	CodeCode Available	0	5
Ensemble Modeling with Contrastive Knowledge Distillation for Sequential Recommendation	Apr 28, 2023	AttributeContrastive Learning	CodeCode Available	0	5
Table Transformers for Imputing Textual Attributes	Aug 4, 2024	ImputationMulti-Task Learning	CodeCode Available	0	5
Graph-Induced Syntactic-Semantic Spaces in Transformer-Based Variational AutoEncoders	Nov 14, 2023	Language ModellingMulti-Task Learning	CodeCode Available	0	5
ENPAR:Enhancing Entity and Entity Pair Representations for Joint Entity Relation Extraction	Apr 1, 2021	coreference-resolutionCoreference Resolution	CodeCode Available	0	5
Bayesian Meta-Learning for Improving Generalizability of Health Prediction Models With Similar Causal Mechanisms	Oct 19, 2023	Meta-LearningMulti-Task Learning	CodeCode Available	0	5
Fine-Tuning Language Models on Multiple Datasets for Citation Intention Classification	Oct 17, 2024	Multi-Task Learning	CodeCode Available	0	5
Graph Neural Networks for Surfactant Multi-Property Prediction	Jan 3, 2024	Ensemble LearningMulti-Task Learning	CodeCode Available	0	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