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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 741–750 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
Improving End-to-End Text Image Translation From the Auxiliary Text Translation Task	Oct 8, 2022	Multi-Task LearningTranslation	CodeCode Available	0	5
Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity	Sep 5, 2019	Language ModelingLanguage Modelling	CodeCode Available	0	5
Integrating Form and Meaning: A Multi-Task Learning Model for Acoustic Word Embeddings	Sep 14, 2022	FormMulti-Task Learning	CodeCode Available	0	5
Deep Cascade Multi-task Learning for Slot Filling in Online Shopping Assistant	Mar 30, 2018	Multi-Task LearningNatural Language Understanding	CodeCode Available	0	5
DeepChest: Dynamic Gradient-Free Task Weighting for Effective Multi-Task Learning in Chest X-ray Classification	May 29, 2025	DiagnosticMulti-Task Learning	CodeCode Available	0	5
Improving Neural Story Generation by Targeted Common Sense Grounding	Aug 26, 2019	Common Sense ReasoningMulti-Task Learning	CodeCode Available	0	5
Deep CNN-based Multi-task Learning for Open-Set Recognition	Mar 7, 2019	DecoderGeneral Classification	CodeCode Available	0	5
DCID: Deep Canonical Information Decomposition	Jun 27, 2023	Information RetrievalMulti-Task Learning	CodeCode Available	0	5
Improving Calibration and Out-of-Distribution Detection in Medical Image Segmentation with Convolutional Neural Networks	Apr 12, 2020	Image SegmentationMedical Image Segmentation	CodeCode Available	0	5
Improved Abdominal Multi-Organ Segmentation via 3D Boundary-Constrained Deep Neural Networks	Oct 9, 2022	DecoderImage Segmentation	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