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 776–800 of 3687 papers

Title	Date	Tasks	Status	Score
Learning a Repression Network for Precise Vehicle Search	Aug 8, 2017	AttributeMulti-Task Learning	CodeCode Available	5
AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning	Nov 27, 2019	Multi-Task LearningSemantic Segmentation	CodeCode Available	5
Improving End-to-End Text Image Translation From the Auxiliary Text Translation Task	Oct 8, 2022	Multi-Task LearningTranslation	CodeCode Available	5
ALUE: Arabic Language Understanding Evaluation	Apr 1, 2021	DiagnosticFairness	CodeCode Available	5
Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled Data	Mar 1, 2019	DenoisingGrammatical Error Correction	CodeCode Available	5
A Syntax-aware Multi-task Learning Framework for Chinese Semantic Role Labeling	Nov 12, 2019	Chinese Semantic Role LabelingMulti-Task Learning	CodeCode Available	5
Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning	Mar 30, 2018	Multi-Task LearningNatural Language Inference	CodeCode Available	5
Improving Dialectal Slot and Intent Detection with Auxiliary Tasks: A Multi-Dialectal Bavarian Case Study	Jan 7, 2025	intent-classificationIntent Classification	CodeCode Available	5
Data Fusion for Multi-Task Learning of Building Extraction and Height Estimation	Aug 5, 2023	Multi-Task Learning	CodeCode Available	5
Asynchronous Multi-Task Learning	Sep 30, 2016	Multi-Task LearningTransfer Learning	CodeCode Available	5
Learning Sparse Sharing Architectures for Multiple Tasks	Nov 12, 2019	Multi-Task Learning	CodeCode Available	5
Data exploitation: multi-task learning of object detection and semantic segmentation on partially annotated data	Nov 7, 2023	Knowledge DistillationMulti-Task Learning	CodeCode Available	5
Improved Abdominal Multi-Organ Segmentation via 3D Boundary-Constrained Deep Neural Networks	Oct 9, 2022	DecoderImage Segmentation	CodeCode Available	5
A Unified Framework for Multi-intent Spoken Language Understanding with prompting	Oct 7, 2022	Intent DetectionMulti-Task Learning	CodeCode Available	5
Inductive biases of multi-task learning and finetuning: multiple regimes of feature reuse	Oct 3, 2023	feature selectionimage-classification	CodeCode Available	5
Multi-task Learning and Catastrophic Forgetting in Continual Reinforcement Learning	Sep 22, 2019	Continual LearningDeep Reinforcement Learning	CodeCode Available	5
Image Captioning with Clause-Focused Metrics in a Multi-Modal Setting for Marketing	May 6, 2019	DescriptiveImage Captioning	CodeCode Available	5
A Unified Mammogram Analysis Method via Hybrid Deep Supervision	Aug 31, 2018	ClassificationGeneral Classification	CodeCode Available	5
Learning to Maximize Mutual Information for Chain-of-Thought Distillation	Mar 5, 2024	Knowledge DistillationLanguage Modeling	CodeCode Available	5
A Survey on Multi-Task Learning	Jul 25, 2017	Active LearningClustering	CodeCode Available	5
Image Splicing Localization Using A Multi-Task Fully Convolutional Network (MFCN)	Sep 6, 2017	Multi-Task Learning	CodeCode Available	5
Learning to Steer by Mimicking Features from Heterogeneous Auxiliary Networks	Nov 7, 2018	Image SegmentationMulti-Task Learning	CodeCode Available	5
Deep Multi-task Representation Learning: A Tensor Factorisation Approach	May 20, 2016	Deep LearningMulti-Task Learning	CodeCode Available	5
Imbalanced multi-label classification using multi-task learning with extractive summarization	Mar 16, 2019	ClassificationExtractive Summarization	CodeCode Available	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	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