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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 1271–1280 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
Can Demographic Factors Improve Text Classification? Revisiting Demographic Adaptation in the Age of Transformers	Oct 13, 2022	Language ModelingLanguage Modelling	CodeCode Available	0	5
End-to-end Multimodal Emotion and Gender Recognition with Dynamic Joint Loss Weights	Sep 4, 2018	Multi-Task Learning	CodeCode Available	0	5
GradCraft: Elevating Multi-task Recommendations through Holistic Gradient Crafting	Jul 29, 2024	Multi-Task LearningRecommendation Systems	CodeCode Available	0	5
MT-CGCNN: Integrating Crystal Graph Convolutional Neural Network with Multitask Learning for Material Property Prediction	Nov 14, 2018	Band GapBIG-bench Machine Learning	CodeCode Available	0	5
CALM: Consensus-Aware Localized Merging for Multi-Task Learning	Jun 16, 2025	Multi-Task LearningTask Arithmetic	CodeCode Available	0	5
GINTRIP: Interpretable Temporal Graph Regression using Information bottleneck and Prototype-based method	Sep 17, 2024	Graph RegressionMulti-Task Learning	CodeCode Available	0	5
GILE: A Generalized Input-Label Embedding for Text Classification	Jun 16, 2018	ClassificationGeneral Classification	CodeCode Available	0	5
Geo-Encoder: A Chunk-Argument Bi-Encoder Framework for Chinese Geographic Re-Ranking	Sep 4, 2023	ChunkingMulti-Task Learning	CodeCode Available	0	5
Giving each task what it needs -- leveraging structured sparsity for tailored multi-task learning	Jun 5, 2024	feature selectionMulti-Task Learning	CodeCode Available	0	5
Byzantine Resilient Distributed Multi-Task Learning	Oct 25, 2020	Multi-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