SOTAVerified|Agents Browse Leaderboard About

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 731–740 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
Is POS Tagging Necessary or Even Helpful for Neural Dependency Parsing?	Mar 6, 2020	Dependency ParsingFeature Engineering	CodeCode Available	0	5
Decoupled and Memory-Reinforced Networks: Towards Effective Feature Learning for One-Step Person Search	Feb 22, 2021	Metric LearningMulti-Task Learning	CodeCode Available	0	5
Improving Sentiment Analysis with Multi-task Learning of Negation	Jun 18, 2019	Multi-Task LearningNegation	CodeCode Available	0	5
Improving Robustness of Neural Machine Translation with Multi-task Learning	Aug 1, 2019	Machine TranslationMulti-Task Learning	CodeCode Available	0	5
A Match Made in Heaven: A Multi-task Framework for Hyperbole and Metaphor Detection	May 27, 2023	Multi-Task Learning	CodeCode Available	0	5
Improving Social Meaning Detection with Pragmatic Masking and Surrogate Fine-Tuning	Aug 1, 2021	DenoisingFew-Shot Learning	CodeCode Available	0	5
A Tree-Structured Multi-Task Model Recommender	Mar 10, 2022	modelMulti-Task Learning	CodeCode Available	0	5
Improving Neural Story Generation by Targeted Common Sense Grounding	Aug 26, 2019	Common Sense ReasoningMulti-Task Learning	CodeCode Available	0	5
Accurate Word Alignment Induction from Neural Machine Translation	Apr 30, 2020	DecoderMachine Translation	CodeCode Available	0	5
A Transformer Framework for Data Fusion and Multi-Task Learning in Smart Cities	Nov 18, 2022	Computational EfficiencyHumanitarian	CodeCode Available	0	5

Show:10 25 50

← PrevPage 74 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