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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 1326–1350 of 3687 papers

TitleStatusHype
BPM_MT: Enhanced Backchannel Prediction Model using Multi-Task Learning—0
Efficient Output Kernel Learning for Multiple Tasks—0
Efficient Multi-task Uncertainties for Joint Semantic Segmentation and Monocular Depth Estimation—0
An Analysis Of Entire Space Multi-Task Models For Post-Click Conversion Prediction—0
Adversarial Transfer Learning for Punctuation Restoration—0
Acquiring Pronunciation Knowledge from Transcribed Speech Audio via Multi-task Learning—0
ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Multi-Task Learning Challenges—0
Efficient Multi-task Prompt Tuning for Recommendation—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
Efficient Meta Lifelong-Learning with Limited Memory—0
Efficiently Identifying Task Groupings for Multi-Task Learning—0
Efficient Low-Resolution Face Recognition via Bridge Distillation—0
BotsTalk: Machine-Sourced Framework for Automatic Curation of Large-scale Multi-skill Dialogue Datasets—0
Analyzing Policy Distillation on Multi-Task Learning and Meta-Reinforcement Learning in Meta-World—0
Efficient Image-Text Retrieval via Keyword-Guided Pre-Screening—0
Efficient Image Gallery Representations at Scale Through Multi-Task Learning—0
Bootstrapping NLU Models with Multi-task Learning—0
Efficient Extraction of Pathologies from C-Spine Radiology Reports using Multi-Task Learning—0
Boosting the Accuracy of Stock Market Prediction via Multi-Layer Hybrid MTL Structure—0
Efficient Deweather Mixture-of-Experts with Uncertainty-aware Feature-wise Linear Modulation—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
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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