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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 121–130 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
DeMT: Deformable Mixer Transformer for Multi-Task Learning of Dense Prediction	Jan 9, 2023	DecoderMulti-Task Learning	CodeCode Available	1	5
Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less Data	Sep 19, 2020	Multi-Task LearningNatural Language Inference	CodeCode Available	1	5
An End-to-End Progressive Multi-Task Learning Framework for Medical Named Entity Recognition and Normalization	Aug 1, 2021	Knowledge GraphsMedical Named Entity Recognition	CodeCode Available	1	5
DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction	Mar 16, 2020	Deep Reinforcement LearningMeta-Learning	CodeCode Available	1	5
Audio-Visual Deception Detection: DOLOS Dataset and Parameter-Efficient Crossmodal Learning	Mar 9, 2023	Deception DetectionMulti-Task Learning	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
Compressed Interaction Graph based Framework for Multi-behavior Recommendation	Mar 4, 2023	Multi-Task Learning	CodeCode Available	1	5
Conflict-Averse Gradient Descent for Multi-task Learning	Oct 26, 2021	Multi-Task Learning	CodeCode Available	1	5
Continuous Urban Change Detection from Satellite Image Time Series with Temporal Feature Refinement and Multi-Task Integration	Jun 25, 2024	Change DetectionMulti-Task Learning	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