SOTAVerified|Agents Browse Leaderboard About Blog

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 3621–3630 of 3687 papers

Title	Date	Tasks	Status	Hype
Predicting Chemical Properties using Self-Attention Multi-task Learning based on SMILES Representation	Oct 19, 2020	Multi-Task LearningRepresentation Learning	CodeCode Available	0
TuckER: Tensor Factorization for Knowledge Graph Completion	May 16, 2019	Knowledge Graph CompletionKnowledge Graphs	CodeCode Available	0
Vision-Based Multi-Task Manipulation for Inexpensive Robots Using End-To-End Learning from Demonstration	Jul 10, 2017	Multi-Task LearningPosition	CodeCode Available	0
The Effects of Multi-Task Learning on ReLU Neural Network Functions	Oct 29, 2024	Multi-Task Learning	CodeCode Available	0
Predicting Multiple Demographic Attributes with Task Specific Embedding Transformation and Attention Network	Mar 25, 2019	AttributeDecision Making	CodeCode Available	0
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
IBCL: Zero-shot Model Generation for Task Trade-offs in Continual Learning	May 24, 2023	Continual Learningimage-classification	CodeCode Available	0
Multi-Task Learning for Features Extraction in Financial Annual Reports	Apr 8, 2024	Multi-Task LearningSentence	CodeCode Available	0
Self-Supervised Learning in Multi-Task Graphs through Iterative Consensus Shift	Mar 26, 2021	Domain AdaptationMulti-Task Learning	CodeCode Available	0
From Low Intrinsic Dimensionality to Non-Vacuous Generalization Bounds in Deep Multi-Task Learning	Jan 31, 2025	Generalization BoundsMulti-Task Learning	CodeCode Available	0

Show:10 25 50

← PrevPage 363 of 369Next →

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