SOTAVerified

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 2326–2350 of 3687 papers

TitleStatusHype
Jointly Learning Clinical Entities and Relations with Contextual Language Models and Explicit Context—0
Sliced Multi-Marginal Optimal Transport—0
Multi-Objective Meta Learning—0
Large-Scale Meta-Learning with Continual Trajectory Shifting—0
Distillation based Multi-task Learning: A Candidate Generation Model for Improving Reading Duration—0
Sequential Recommendation in Online Games with Multiple Sequences, Tasks and User Levels—0
Multi-Task Self-Supervised Pre-Training for Music Classification—0
Hierarchical Ranking for Answer Selection—0
Learning Twofold Heterogeneous Multi-Task by Sharing Similar Convolution Kernel Pairs—0
Copula-based conformal prediction for Multi-Target Regression—0
Exploring multi-task multi-lingual learning of transformer models for hate speech and offensive speech identification in social mediaCode0
Language Modelling as a Multi-Task Problem—0
Multi-Modal Aesthetic Assessment for MObile Gaming Image—0
Muppet: Massive Multi-task Representations with Pre-FinetuningCode0
Network Clustering for Multi-task Learning—0
SOSD-Net: Joint Semantic Object Segmentation and Depth Estimation from Monocular images—0
Deep Multi-Task Learning for Joint Localization, Perception, and Prediction—0
Task-driven Self-supervised Bi-channel Networks for Diagnosis of Breast Cancers with Mammography—0
SoftNER: Mining Knowledge Graphs From Cloud Incidents—0
End-to-End Speaker Height and age estimation using Attention Mechanism with LSTM-RNN—0
Seed Stocking Via Multi-Task Learning—0
DBTagger: Multi-Task Learning for Keyword Mapping in NLIDBs Using Bi-Directional Recurrent Neural NetworksCode0
Transfer Learning and Augmentation for Word Sense Disambiguation—0
Joint Prediction of Remaining Useful Life and Failure Type of Train Wheelsets: A Multi-task Learning Approach—0
Spatial Object Recommendation with Hints: When Spatial Granularity Matters—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