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 2376–2400 of 3687 papers

TitleStatusHype
Multi-Task Learning of System Dialogue Act Selection for Supervised Pretraining of Goal-Oriented Dialogue Policies—0
Multitask Learning of Temporal Connectionism in Convolutional Networks using a Joint Distribution Loss Function to Simultaneously Identify Tools and Phase in Surgical Videos—0
Multi-task learning of time series and its application to the travel demand—0
Multi-task Learning on MNIST Image Datasets—0
Multi-Task Learning on Networks—0
Transporters with Visual Foresight for Solving Unseen Rearrangement Tasks—0
Multi-task Learning over Graph Structures—0
Multi-Task Learning Regression via Convex Clustering—0
Multi-Task Learning to Capture Changes in Mood Over Time—0
Multi-task Learning to Enable Location Mention Identification in the Early Hours of a Crisis Event—0
Multi-Task Learning to Enhance Generalizability of Neural Network Equalizers in Coherent Optical Systems—0
Multi-task learning to improve natural language understanding—0
Multi-task Learning To Improve Semantic Segmentation Of CBCT Scans Using Image Reconstruction—0
Multi-task Learning Using a Combination of Contextualised and Static Word Embeddings for Arabic Sarcasm Detection and Sentiment Analysis—0
Multi-Task Learning using AraBert for Offensive Language Detection—0
Multi-Task Learning using Dynamic Task Weighting for Conversational Question Answering—0
Multi-Task Learning Using Neighborhood Kernels—0
Multitask Learning using Task Clustering with Applications to Predictive Modeling and GWAS of Plant Varieties—0
A Real-Time Multi-Task Learning System for Joint Detection of Face, Facial Landmark and Head Pose—0
Multi-Task Learning Using Uncertainty to Weigh Losses for Heterogeneous Face Attribute Estimation—0
Multi-task Learning via Adaptation to Similar Tasks for Mortality Prediction of Diverse Rare Diseases—0
Multi-Task Learning via Co-Attentive Sharing for Pedestrian Attribute Recognition—0
Multi-Task Learning via Conic Programming—0
Multi-task learning via robust regularized clustering with non-convex group penalties—0
Multi-Task Learning via Scale Aware Feature Pyramid Networks and Effective Joint Head—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