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 181–190 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
Encoding formulas as deep networks: Reinforcement learning for zero-shot execution of LTL formulas	Jun 1, 2020	MinecraftMulti-Task Learning	CodeCode Available	1	5
Encoding Visual Attributes in Capsules for Explainable Medical Diagnoses	Sep 12, 2019	AttributeLung Cancer Diagnosis	CodeCode Available	1	5
Achelous++: Power-Oriented Water-Surface Panoptic Perception Framework on Edge Devices based on Vision-Radar Fusion and Pruning of Heterogeneous Modalities	Dec 14, 2023	Autonomous NavigationMulti-Task Learning	CodeCode Available	1	5
A Unified Span-Based Approach for Opinion Mining with Syntactic Constituents	Jun 1, 2021	Multi-Task LearningOpinion Mining	CodeCode Available	1	5
ENHANCE (ENriching Health data by ANnotations of Crowd and Experts): A case study for skin lesion classification	Jul 27, 2021	DiagnosticLesion Classification	CodeCode Available	1	5
Auto-Lambda: Disentangling Dynamic Task Relationships	Feb 7, 2022	Auxiliary LearningMeta-Learning	CodeCode Available	1	5
Automatic Severity Classification of Dysarthric speech by using Self-supervised Model with Multi-task Learning	Oct 27, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available	1	5
DeepCVA: Automated Commit-level Vulnerability Assessment with Deep Multi-task Learning	Aug 18, 2021	Multi-Task Learning	CodeCode Available	1	5
A Multi-Head Ensemble Multi-Task Learning Approach for Dynamical Computation Offloading	Sep 2, 2023	Edge-computingMulti-Task Learning	CodeCode Available	1	5
An Investigation of End-to-End Models for Robust Speech Recognition	Feb 11, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available	1	5

Show:10 25 50

← PrevPage 19 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