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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 171–180 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
ATTEMPT: Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft Prompts	May 24, 2022	Few-Shot LearningLanguage Modelling	CodeCode Available	1	5
DESCN: Deep Entire Space Cross Networks for Individual Treatment Effect Estimation	Jul 19, 2022	Causal InferenceMulti-Task Learning	CodeCode Available	1	5
Annotating Columns with Pre-trained Language Models	Apr 5, 2021	Columns Property AnnotationColumn Type Annotation	CodeCode Available	1	5
Detection-Correction Structure via General Language Model for Grammatical Error Correction	May 28, 2024	Grammatical Error CorrectionLanguage Modeling	CodeCode Available	1	5
Anomaly Detection in Video via Self-Supervised and Multi-Task Learning	Nov 15, 2020	Abnormal Event Detection In VideoAnomaly Detection	CodeCode Available	1	5
Does Text Attract Attention on E-Commerce Images: A Novel Saliency Prediction Dataset and Method	Jan 1, 2022	Multi-Task LearningSaliency Prediction	CodeCode Available	1	5
Allophant: Cross-lingual Phoneme Recognition with Articulatory Attributes	Jun 7, 2023	AttributeCross-Lingual Transfer	CodeCode Available	1	5
DUET: Cross-modal Semantic Grounding for Contrastive Zero-shot Learning	Jul 4, 2022	AttributeContrastive Learning	CodeCode Available	1	5
AdaTT: Adaptive Task-to-Task Fusion Network for Multitask Learning in Recommendations	Apr 11, 2023	Multi-Task Learning	CodeCode Available	1	5
An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment Analysis	Jun 17, 2019	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	1	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