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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 881–890 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
iCLIP: Bridging Image Classification and Contrastive Language-Image Pre-Training for Visual Recognition	Jan 1, 2023	Classificationimage-classification	CodeCode Available	0	5
Multi-task Geometric Estimation of Depth and Surface Normal from Monocular 360° Images	Nov 4, 2024	Multi-Task LearningScene Understanding	CodeCode Available	0	5
Identification of Distorted RF Components via Deep Multi-Task Learning	Jul 4, 2022	Multi-Task Learning	CodeCode Available	0	5
Image Captioning with Clause-Focused Metrics in a Multi-Modal Setting for Marketing	May 6, 2019	DescriptiveImage Captioning	CodeCode Available	0	5
iACOS: Advancing Implicit Sentiment Extraction with Informative and Adaptive Negative Examples	Nov 7, 2023	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	0	5
Multi-Tasking Genetic Algorithm (MTGA) for Fuzzy System Optimization	Dec 15, 2018	Multi-Task Learning	CodeCode Available	0	5
Cross-Task Consistency Learning Framework for Multi-Task Learning	Nov 28, 2021	Contrastive LearningMulti-Task Learning	CodeCode Available	0	5
Multi-Task Learning Approach for Unified Biometric Estimation from Fetal Ultrasound Anomaly Scans	Nov 16, 2023	ClassificationMulti-Task Learning	CodeCode Available	0	5
Ask Question First for Enhancing Lifelong Language Learning	Aug 17, 2022	Language ModelingLanguage Modelling	CodeCode Available	0	5
IBCL: Zero-shot Model Generation for Task Trade-offs in Continual Learning	Oct 4, 2023	Continual Learningimage-classification	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