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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 851–875 of 3687 papers

TitleStatusHype
Deep Learning for Automatic Quality Grading of Mangoes: Methods and Insights—0
DFGET: Displacement-Field Assisted Graph Energy Transmitter for Gland Instance Segmentation—0
DG-PIC: Domain Generalized Point-In-Context Learning for Point Cloud Understanding—0
DGRC: An Effective Fine-tuning Framework for Distractor Generation in Chinese Multi-choice Reading Comprehension—0
DG-STMTL: A Novel Graph Convolutional Network for Multi-Task Spatio-Temporal Traffic Forecasting—0
Diabetic retinopathy image classification method based on GreenBen data augmentation—0
DiagrammaticLearning: A Graphical Language for Compositional Training Regimes—0
DialogAct2Vec: Towards End-to-End Dialogue Agent by Multi-Task Representation Learning—0
DiaNet: BERT and Hierarchical Attention Multi-Task Learning of Fine-Grained Dialect—0
Different Absorption from the Same Sharing: Sifted Multi-task Learning for Fake News Detection—0
Differentiable Mask for Pruning Convolutional and Recurrent Networks—0
Differentially Private Transferrable Deep Learning with Membership-Mappings—0
A Multi-modal and Multi-task Learning Method for Action Unit and Expression Recognition—0
Deep Learning Enabled Segmentation, Classification and Risk Assessment of Cervical Cancer—0
DiGrad: Multi-Task Reinforcement Learning with Shared Actions—0
A region and category confidence-based multi-task network for carotid ultrasound image segmentation and classification—0
Dining on Details: LLM-Guided Expert Networks for Fine-Grained Food Recognition—0
AuxNet: Auxiliary tasks enhanced Semantic Segmentation for Automated Driving—0
Directly Optimizing IoU for Bounding Box Localization—0
Direct Preference Optimization-Enhanced Multi-Guided Diffusion Model for Traffic Scenario Generation—0
Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks—0
3D medical image segmentation with labeled and unlabeled data using autoencoders at the example of liver segmentation in CT images—0
Embracing the Disharmony in Medical Imaging: A Simple and Effective Framework for Domain Adaptation—0
Discovering Collaborative Signals for Next POI Recommendation with Iterative Seq2Graph Augmentation—0
Enabling Asymmetric Knowledge Transfer in Multi-Task Learning with Self-Auxiliaries—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