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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 301–310 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
Bi-Directional Attention for Joint Instance and Semantic Segmentation in Point Clouds	Mar 11, 2020	Instance SegmentationMulti-Task Learning	CodeCode Available	1	5
A Simple and Efficient Multi-Task Learning Approach for Conditioned Dialogue Generation	Oct 21, 2020	Dialogue GenerationLanguage Modelling	CodeCode Available	1	5
An End-to-End Progressive Multi-Task Learning Framework for Medical Named Entity Recognition and Normalization	Aug 1, 2021	Knowledge GraphsMedical Named Entity Recognition	CodeCode Available	1	5
BoIR: Box-Supervised Instance Representation for Multi-Person Pose Estimation	Sep 25, 2023	DisentanglementKeypoint Estimation	CodeCode Available	1	5
AIONER: All-in-one scheme-based biomedical named entity recognition using deep learning	Nov 30, 2022	AllMulti-Task Learning	CodeCode Available	1	5
Global-Reasoned Multi-Task Learning Model for Surgical Scene Understanding	Jan 28, 2022	Graph AttentionKnowledge Distillation	CodeCode Available	1	5
Automatic Charge Identification from Facts: A Few Sentence-Level Charge Annotations is All You Need	Dec 1, 2020	AllMulti-Task Learning	CodeCode Available	1	5
Enhancing Label Correlation Feedback in Multi-Label Text Classification via Multi-Task Learning	Jun 6, 2021	DiversityMulti Label Text Classification	CodeCode Available	1	5
Gradient Surgery for Multi-Task Learning	Jan 19, 2020	Deep Reinforcement Learningimage-classification	CodeCode Available	1	5
Exploiting Shared Representations for Personalized Federated Learning	Feb 14, 2021	Federated LearningMeta-Learning	CodeCode Available	1	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