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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 3081–3090 of 3687 papers

Title	Date	Tasks	Status	Hype
Multi-Task Learning with Group-Specific Feature Space Sharing	Aug 13, 2015	Binary ClassificationMulti-Task Learning	CodeCode Available	0
Instruction Tuned Models are Quick Learners	May 17, 2023	In-Context LearningMulti-Task Learning	CodeCode Available	0
Learning End-to-end Autonomous Driving using Guided Auxiliary Supervision	Aug 30, 2018	Autonomous DrivingMulti-Task Learning	CodeCode Available	0
REG: Refined Generalized Focal Loss for Road Asset Detection on Thai Highways Using Vision-Based Detection and Segmentation Models	Sep 15, 2024	Multi-Task LearningSegmentation	CodeCode Available	0
A Hierarchical Multi-task Approach for Learning Embeddings from Semantic Tasks	Nov 14, 2018	Inductive BiasMulti-Task Learning	CodeCode Available	0
Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity	Sep 5, 2019	Language ModelingLanguage Modelling	CodeCode Available	0
Building a Dialogue Corpus Annotated with Expressed and Experienced Emotions	May 24, 2022	Emotion RecognitionMulti-Task Learning	CodeCode Available	0
Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal	Dec 7, 2017	Generative Adversarial NetworkMulti-Task Learning	CodeCode Available	0
Bowtie Networks: Generative Modeling for Joint Few-Shot Recognition and Novel-View Synthesis	Aug 16, 2020	Data AugmentationMulti-Task Learning	CodeCode Available	0
Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness	Mar 31, 2023	Multi-Task LearningTransfer Learning	CodeCode Available	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