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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 711–720 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
A Multi-lingual Multi-task Architecture for Low-resource Sequence Labeling	Jul 1, 2018	Abstractive Text SummarizationMachine Translation	CodeCode Available	0	5
Incomplete Utterance Rewriting with Editing Operation Guidance and Utterance Augmentation	Mar 20, 2025	Multi-Task Learning	CodeCode Available	0	5
AudioLog: LLMs-Powered Long Audio Logging with Hybrid Token-Semantic Contrastive Learning	Nov 21, 2023	Acoustic Scene ClassificationAudio captioning	CodeCode Available	0	5
Achievement-Based Training Progress Balancing for Multi-Task Learning	Jan 1, 2023	Depth EstimationMulti-Task Learning	CodeCode Available	0	5
Attentive Task Interaction Network for Multi-Task Learning	Jan 25, 2022	DecoderKnowledge Distillation	CodeCode Available	0	5
A Modulation Module for Multi-task Learning with Applications in Image Retrieval	Jul 17, 2018	Image RetrievalMulti-Task Learning	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
Improving Sentiment Analysis with Multi-task Learning of Negation	Jun 18, 2019	Multi-Task LearningNegation	CodeCode Available	0	5
Attentive History Selection for Conversational Question Answering	Aug 26, 2019	Conversational Question AnsweringConversational Search	CodeCode Available	0	5
Improving End-to-End Text Image Translation From the Auxiliary Text Translation Task	Oct 8, 2022	Multi-Task LearningTranslation	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