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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 801–810 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
Image Captioning with Clause-Focused Metrics in a Multi-Modal Setting for Marketing	May 6, 2019	DescriptiveImage Captioning	CodeCode Available	0	5
Let-Mi: An Arabic Levantine Twitter Dataset for Misogynistic Language	Mar 18, 2021	Multi-Task Learning	CodeCode Available	0	5
Inductive biases of multi-task learning and finetuning: multiple regimes of feature reuse	Oct 3, 2023	feature selectionimage-classification	CodeCode Available	0	5
Improving Dialectal Slot and Intent Detection with Auxiliary Tasks: A Multi-Dialectal Bavarian Case Study	Jan 7, 2025	intent-classificationIntent Classification	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
Leveraging Multi-domain, Heterogeneous Data using Deep Multitask Learning for Hate Speech Detection	Mar 23, 2021	Hate Speech DetectionMulti-Task Learning	CodeCode Available	0	5
Interpetable Target-Feature Aggregation for Multi-Task Learning based on Bias-Variance Analysis	Jun 12, 2024	ClusteringDimensionality Reduction	CodeCode Available	0	5
iCLIP: Bridging Image Classification and Contrastive Language-Image Pre-Training for Visual Recognition	Jan 1, 2023	Classificationimage-classification	CodeCode Available	0	5
DaN+: Danish Nested Named Entities and Lexical Normalization	May 24, 2021	Cross-Lingual TransferLexical Normalization	CodeCode Available	0	5
Identification of Distorted RF Components via Deep Multi-Task Learning	Jul 4, 2022	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