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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 3126–3150 of 3687 papers

TitleStatusHype
A Syntax-aware Multi-task Learning Framework for Chinese Semantic Role LabelingCode0
Improving Sentiment Analysis with Multi-task Learning of NegationCode0
Improving Robustness of Neural Machine Translation with Multi-task LearningCode0
Boundary-aware Context Neural Network for Medical Image SegmentationCode0
Cross-Stitched Multi-task Dual Recursive Networks for Unified Single Image Deraining and DesnowingCode0
Representation Disentanglement for Multi-task Learning with application to Fetal UltrasoundCode0
Learning to Make Predictions on Graphs with AutoencodersCode0
Learning to Maximize Mutual Information for Chain-of-Thought DistillationCode0
Learning to Multi-Task by Active SamplingCode0
STG-MTL: Scalable Task Grouping for Multi-Task Learning Using Data MapCode0
ST-MTL: Spatio-Temporal Multitask Learning Model to Predict Scanpath While Tracking Instruments in Robotic SurgeryCode0
Cross-Domain Self-supervised Multi-task Feature Learning using Synthetic ImageryCode0
Improving Relation Extraction by Leveraging Knowledge Graph Link PredictionCode0
Multi-Task Neural Models for Translating Between Styles Within and Across LanguagesCode0
Understanding COVID-19 Vaccine Campaign on Facebook using Minimal SupervisionCode0
Towards Explainable Multimodal Depression Recognition for Clinical InterviewsCode0
Improving Neural Story Generation by Targeted Common Sense GroundingCode0
Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled DataCode0
Learning to Represent Bilingual DictionariesCode0
Critical Learning Periods Emerge Even in Deep Linear NetworksCode0
Bi-Preference Learning Heterogeneous Hypergraph Networks for Session-based RecommendationCode0
Learning to Steer by Mimicking Features from Heterogeneous Auxiliary NetworksCode0
Asynchronous Multi-Task LearningCode0
Learning to Transfer for Traffic Forecasting via Multi-task LearningCode0
Residual Multi-Task Learner for Applied RankingCode0
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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