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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 1291–1300 of 3687 papers

Title	Date	Tasks	Status	Hype
Constraint-driven multi-task learning	Aug 24, 2022	Inductive logic programmingMulti-Task Learning	—Unverified	0
How Vital is the Jurisprudential Relevance: Law Article Intervened Legal Case Retrieval and Matching	Feb 25, 2025	Multi-Task LearningRetrieval	—Unverified	0
Global Inference for Aspect and Opinion Terms Co-Extraction Based on Multi-Task Neural Networks	Oct 10, 2018	Aspect Term Extraction and Sentiment ClassificationMulti-Task Learning	—Unverified	0
How Self-Supervised Learning Can be Used for Fine-Grained Head Pose Estimation?	Aug 10, 2021	Head Pose EstimationMulti-Task Learning	—Unverified	0
Fusion of Multispectral Data Through Illumination-aware Deep Neural Networks for Pedestrian Detection	Feb 27, 2018	Autonomous DrivingMultispectral Object Detection	—Unverified	0
How to Ask Good Questions? Try to Leverage Paraphrases	Jul 1, 2020	DiversityMulti-Task Learning	—Unverified	0
GMP-TL: Gender-augmented Multi-scale Pseudo-label Enhanced Transfer Learning for Speech Emotion Recognition	May 3, 2024	Emotion RecognitionMulti-Task Learning	—Unverified	0
Go Figure! Multi-task transformer-based architecture for metaphor detection using idioms: ETS team in 2020 metaphor shared task	Jul 1, 2020	Multi-Task Learning	—Unverified	0
A Joint Learning Framework With BERT for Spoken Language Understanding	Nov 20, 2019	Decoderintent-classification	—Unverified	0
How Far Can We Go with Data Selection? A Case Study on Semantic Sequence Tagging Tasks	Nov 1, 2020	Multi-Task LearningTransfer Learning	—Unverified	0

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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