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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 1751–1800 of 3687 papers

TitleStatusHype
A Benchmark for Federated Hetero-Task Learning—0
Collaborative Optimization in Financial Data Mining Through Deep Learning and ResNeXt—0
Learning More for Free - A Multi Task Learning Approach for Improved Pathology Classification in Capsule Endoscopy—0
Discriminatory Transfer—0
FedBone: Towards Large-Scale Federated Multi-Task Learning—0
Disentangled Interleaving Variational Encoding—0
Learning Multiple Tasks with Multilinear Relationship Networks—0
Learning Multiple Visual Tasks while Discovering their Structure—0
Collaborative Multi-Task Representation for Natural Language Understanding—0
Learning Multi-Task Transferable Rewards via Variational Inverse Reinforcement Learning—0
Disentangling Representations through Multi-task Learning—0
Learning Optical Flow, Depth, and Scene Flow without Real-World Labels—0
Learning Partially Aligned Item Representation for Cross-Domain Sequential Recommendation—0
Learning Predictive, Online Approximations of Explanatory, Offline Algorithms—0
Learning Rates for Multi-task Regularization Networks—0
Distance Correlation Based Brain Functional Connectivity Estimation and Non-Convex Multi-Task Learning for Developmental fMRI Studies—0
An Iterative Polishing Framework based on Quality Aware Masked Language Model for Chinese Poetry Generation—0
Learning representations for sentiment classification using Multi-task framework—0
Learning Representations for Text-level Discourse Parsing—0
Learning Shared Dynamics with Meta-World Models—0
Distillation based Multi-task Learning: A Candidate Generation Model for Improving Reading Duration—0
FedAuxHMTL: Federated Auxiliary Hard-Parameter Sharing Multi-Task Learning for Network Edge Traffic Classification—0
Learning Task Grouping and Overlap in Multi-task Learning—0
Learning Task Relatedness in Multi-Task Learning for Images in Context—0
Collaborative Learning with Different Labeling Functions—0
An Iteratively Re-weighted Method for Problems with Sparsity-Inducing Norms—0
Learning to Branch for Multi-Task Learning—0
Distributed Multitask Learning—0
Feature Representation Learning for NL2SQL Generation Based on Coupling and Decoupling—0
Distributed Multi-Task Learning for Stochastic Bandits with Context Distribution and Stage-wise Constraints—0
Learning to Generate Questions by Learning What not to Generate—0
Feature Partitioning for Efficient Multi-Task Architectures—0
Collaborative Learning for Deep Neural Networks—0
Learning to Initialize: Can Meta Learning Improve Cross-task Generalization in Prompt Tuning?—0
Learning to Jointly Generate and Separate Reflections—0
Learning to Learn Weight Generation via Local Consistency Diffusion—0
Distributed Primal-Dual Optimization for Online Multi-Task Learning—0
A Multi-Task Learning & Generation Framework: Valence-Arousal, Action Units & Primary Expressions—0
Distributed Stochastic Multi-Task Learning with Graph Regularization—0
Learning to Multi-Task Learn for Better Neural Machine Translation—0
Aggressive Language Detection with Joint Text Normalization via Adversarial Multi-task Learning—0
Learning to optimize by multi-gradient for multi-objective optimization—0
Adapt-and-Adjust: Overcoming the Long-Tail Problem of Multilingual Speech Recognition—0
Learning to Profile: User Meta-Profile Network for Few-Shot Learning—0
Learning to Push by Grasping: Using multiple tasks for effective learning—0
Learning to Recommend with Multiple Cascading Behaviors—0
Collaborative and Efficient Personalization with Mixtures of Adaptors—0
Feature-informed Latent Space Regularization for Music Source Separation—0
Location-Centered House Price Prediction: A Multi-Task Learning Approach—0
CoinRobot: Generalized End-to-end Robotic Learning for Physical Intelligence—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