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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 721–730 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
A Method for Discovering Novel Classes in Tabular Data	Sep 2, 2022	Multi-Task LearningNovel Class Discovery	CodeCode Available	0	5
Attention-based multi-task learning for speech-enhancement and speaker-identification in multi-speaker dialogue scenario	Jan 7, 2021	Multi-Task LearningSpeaker Identification	CodeCode Available	0	5
Attention-Augmented End-to-End Multi-Task Learning for Emotion Prediction from Speech	Mar 29, 2019	Emotion RecognitionMulti-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
Incorporating Singletons and Mention-based Features in Coreference Resolution via Multi-task Learning for Better Generalization	Sep 20, 2023	coreference-resolutionCoreference Resolution	CodeCode Available	0	5
Instruction Tuned Models are Quick Learners	May 17, 2023	In-Context LearningMulti-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
A Tree-Structured Multi-Task Model Recommender	Mar 10, 2022	modelMulti-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

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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