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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 1171–1180 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
KFC: Kinship Verification with Fair Contrastive Loss and Multi-Task Learning	Sep 19, 2023	Face VerificationFairness	CodeCode Available	0	5
Graph-Induced Syntactic-Semantic Spaces in Transformer-Based Variational AutoEncoders	Nov 14, 2023	Language ModellingMulti-Task Learning	CodeCode Available	0	5
CeViT: Copula-Enhanced Vision Transformer in multi-task learning and bi-group image covariates with an application to myopia screening	Jan 11, 2025	Multi-Task Learning	CodeCode Available	0	5
Knowing Earlier what Right Means to You: A Comprehensive VQA Dataset for Grounding Relative Directions via Multi-Task Learning	Jul 6, 2022	DiagnosticMulti-Task Learning	CodeCode Available	0	5
ESM-NBR: fast and accurate nucleic acid-binding residue prediction via protein language model feature representation and multi-task learning	Dec 1, 2023	Language ModelingLanguage Modelling	CodeCode Available	0	5
Graph Neural Networks for Surfactant Multi-Property Prediction	Jan 3, 2024	Ensemble LearningMulti-Task Learning	CodeCode Available	0	5
ERNIE 3.0 Tiny: Frustratingly Simple Method to Improve Task-Agnostic Distillation Generalization	Jan 9, 2023	Knowledge DistillationLanguage Modelling	CodeCode Available	0	5
Graph-based Knowledge Distillation by Multi-head Attention Network	Jul 4, 2019	Inductive BiasKnowledge Distillation	CodeCode Available	0	5
Graph Star Net for Generalized Multi-Task Learning	Jun 21, 2019	ClassificationGeneral Classification	CodeCode Available	0	5
Implicit Geometry and Interaction Embeddings Improve Few-Shot Molecular Property Prediction	Feb 4, 2023	Few-Shot LearningMolecular Docking	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