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 1881–1890 of 3687 papers

Title	Date	Tasks	Status	Hype
On Steering Multi-Annotations per Sample for Multi-Task Learning	Mar 6, 2022	Instance SegmentationMulti-Task Learning	—Unverified	0
Min-Max Bilevel Multi-objective Optimization with Applications in Machine Learning	Mar 3, 2022	BIG-bench Machine LearningBilevel Optimization	CodeCode Available	0
Fine-grained Urban Flow Inference with Incomplete Data	Mar 1, 2022	Fine-Grained Urban Flow InferenceMulti-Task Learning	CodeCode Available	0
Multi-Task Multi-Scale Learning For Outcome Prediction in 3D PET Images	Mar 1, 2022	Inductive BiasMulti-Task Learning	—Unverified	0
HyperPrompt: Prompt-based Task-Conditioning of Transformers	Mar 1, 2022	Computational EfficiencyMulti-Task Learning	—Unverified	0
Weakly Supervised Learning for cell recognition in immunohistochemical cytoplasm staining images	Feb 27, 2022	Multi-Task LearningRepresentation Learning	—Unverified	0
Short-term passenger flow prediction for multi-traffic modes: A Transformer and residual network based multi-task learning method	Feb 27, 2022	Multi-Task Learning	—Unverified	0
Multi-task Learning Approach for Modulation and Wireless Signal Classification for 5G and Beyond: Edge Deployment via Model Compression	Feb 26, 2022	ManagementModel Compression	—Unverified	0
NeuralHOFusion: Neural Volumetric Rendering under Human-object Interactions	Feb 25, 2022	Human-Object Interaction DetectionMulti-Task Learning	—Unverified	0
The Reality of Multi-Lingual Machine Translation	Feb 25, 2022	Cross-Lingual TransferMachine Translation	—Unverified	0

Show:10 25 50

← PrevPage 189 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