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 231–240 of 3687 papers

Title	Date	Tasks	Status	Hype
Push-the-Boundary: Boundary-aware Feature Propagation for Semantic Segmentation of 3D Point Clouds	Dec 23, 2022	Multi-Task LearningObject	CodeCode Available	1
Dataless Knowledge Fusion by Merging Weights of Language Models	Dec 19, 2022	Multi-Task Learning	CodeCode Available	1
OFASys: A Multi-Modal Multi-Task Learning System for Building Generalist Models	Dec 8, 2022	Multi-Task Learning	CodeCode Available	1
What do you MEME? Generating Explanations for Visual Semantic Role Labelling in Memes	Dec 1, 2022	MarketingMulti-Task Learning	CodeCode Available	1
AIONER: All-in-one scheme-based biomedical named entity recognition using deep learning	Nov 30, 2022	AllMulti-Task Learning	CodeCode Available	1
Global and Local Hierarchy-aware Contrastive Framework for Implicit Discourse Relation Recognition	Nov 25, 2022	Contrastive LearningMulti-Task Learning	CodeCode Available	1
Multi-Task Learning of Object State Changes from Uncurated Videos	Nov 24, 2022	Multi-Task LearningObject	CodeCode Available	1
Unified Multimodal Model with Unlikelihood Training for Visual Dialog	Nov 23, 2022	Answer GenerationChatbot	CodeCode Available	1
Multi-task Learning for Camera Calibration	Nov 22, 2022	3D ReconstructionAutonomous Driving	CodeCode Available	1
Multi-task Learning for Sparse Traffic Forecasting	Nov 18, 2022	Graph Neural NetworkMulti-Task Learning	CodeCode Available	1

Show:10 25 50

← PrevPage 24 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