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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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1526–1550 of 3687 papers

TitleStatusHype
Multi-Task Learning with Prior Information—0
Machine Learning Approach to Polymerization Reaction Engineering: Determining Monomers Reactivity Ratios—0
PMT-IQA: Progressive Multi-task Learning for Blind Image Quality AssessmentCode0
EMT-NAS:Transferring Architectural Knowledge Between Tasks From Different DatasetsCode0
Mod-Squad: Designing Mixtures of Experts As Modular Multi-Task Learners—0
SmartAssign: Learning a Smart Knowledge Assignment Strategy for Deraining and Desnowing—0
MetaBEV: Solving Sensor Failures for 3D Detection and Map Segmentation—0
Achievement-Based Training Progress Balancing for Multi-Task LearningCode0
Multi-Task Learning with Knowledge Distillation for Dense Prediction—0
iCLIP: Bridging Image Classification and Contrastive Language-Image Pre-Training for Visual RecognitionCode0
Masked Representation Learning for Domain Generalized Stereo Matching—0
Hierarchical Prompt Learning for Multi-Task Learning—0
CORE: Co-planarity Regularized Monocular Geometry Estimation with Weak Supervision—0
CO-Net: Learning Multiple Point Cloud Tasks at Once with A Cohesive Network—0
FedICT: Federated Multi-task Distillation for Multi-access Edge ComputingCode0
AdaMV-MoE: Adaptive Multi-Task Vision Mixture-of-Experts—0
Multi-Label Compound Expression Recognition: C-EXPR Database & Network—0
Reconciling Object-Level and Global-Level Objectives for Long-Tail DetectionCode0
Poly-PC: A Polyhedral Network for Multiple Point Cloud Tasks at Once—0
TA-DA: Topic-Aware Domain Adaptation for Scientific Keyphrase Identification and Classification (Student Abstract)—0
A Deep Learning Method for Real-time Bias Correction of Wind Field Forecasts in the Western North Pacific—0
Personalized Decentralized Multi-Task Learning Over Dynamic Communication Graphs—0
MoQuad: Motion-focused Quadruple Construction for Video Contrastive Learning—0
Positive-incentive Noise—0
Improving Cross-task Generalization of Unified Table-to-text Models with Compositional Task Configurations—0
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All datasetsQM9Cityscapes testNYUv2OMNIGLOTCelebAUTKFacewireframe dataset

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PCGrad∆m%125.7—Unverified
2CAGrad∆m%112.8—Unverified
3IMTL-G∆m%77.2—Unverified
4Nash-MTL∆m%62—Unverified
5BayesAgg-MTL∆m%53.7—Unverified
#ModelMetricClaimedVerifiedStatus
1SwinMTLmIoU76.41—Unverified
2Nash-MTLmIoU75.41—Unverified
3MultiObjectiveOptimizationmIoU66.63—Unverified
#ModelMetricClaimedVerifiedStatus
1SwinMTLMean IoU58.14—Unverified
2Nash-MTLMean IoU40.13—Unverified
#ModelMetricClaimedVerifiedStatus
1Gumbel-Matrix RoutingAverage Accuracy93.52—Unverified
2Mixture-of-ExpertsAverage Accuracy92.19—Unverified
#ModelMetricClaimedVerifiedStatus
1MGDA-UBError8.25—Unverified
#ModelMetricClaimedVerifiedStatus
1BayesAgg-MTLdelta_m-2.23—Unverified
#ModelMetricClaimedVerifiedStatus
1LETRFH83.3—Unverified