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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 601–625 of 3687 papers

TitleStatusHype
Deep Multi-Task Learning for Anomalous Driving Detection Using CAN Bus Scalar Sensor Data—0
Bounds for Vector-Valued Function Estimation—0
BoundMatch: Boundary detection applied to semi-supervised segmentation for urban-driving scenes—0
Analyzing the Effect of Multi-task Learning for Biomedical Named Entity Recognition—0
Analyzing Policy Distillation on Multi-Task Learning and Meta-Reinforcement Learning in Meta-World—0
BotsTalk: Machine-Sourced Framework for Automatic Curation of Large-scale Multi-skill Dialogue Datasets—0
ABAW: Learning from Synthetic Data & Multi-Task Learning Challenges—0
Cross-domain Named Entity Recognition via Graph Matching—0
Bootstrapping NLU Models with Multi-task Learning—0
Boosting the Accuracy of Stock Market Prediction via Multi-Layer Hybrid MTL Structure—0
Boosting Share Routing for Multi-task Learning—0
Boosting Facial Action Unit Detection Through Jointly Learning Facial Landmark Detection and Domain Separation and Reconstruction—0
Analyzing Learned Representations of a Deep ASR Performance Prediction Model—0
ACQ: A Unified Framework for Automated Programmatic Creativity in Online Advertising—0
Deep Mixture of Diverse Experts for Large-Scale Visual Recognition—0
Body Segmentation Using Multi-task Learning—0
Analytical Uncertainty-Based Loss Weighting in Multi-Task Learning—0
Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting—0
Adversarial multi-task learning to solve holistic semantic polishing problem of Chinese text—0
Deep Learning for Automatic Quality Grading of Mangoes: Methods and Insights—0
Biomedical Event Extraction as Sequence Labeling—0
BioInstruct: Instruction Tuning of Large Language Models for Biomedical Natural Language Processing—0
Adversarial Multi-task Learning for Text Classification—0
Billion-Scale Pretraining with Vision Transformers for Multi-Task Visual Representations—0
Bilingually-constrained Synthetic Data for Implicit Discourse Relation Recognition—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