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 2351–2375 of 3687 papers

TitleStatusHype
Contextual Classification Using Self-Supervised Auxiliary Models for Deep Neural NetworksCode0
Attention-based multi-task learning for speech-enhancement and speaker-identification in multi-speaker dialogue scenarioCode0
Weakly Supervised Multi-Object Tracking and Segmentation—0
Learning With Privileged Tasks—0
Graph-BAS3Net: Boundary-Aware Semi-Supervised Segmentation Network With Bilateral Graph Convolution—0
HyperGrid Transformers: Towards A Single Model for Multiple Tasks—0
Information Transfer in Multi-Task Learning—0
Intra-layer Neural Architecture Search—0
Learning Multiple Pixelwise Tasks Based on Loss Scale BalancingCode0
Disentangled Representation for Age-Invariant Face Recognition: A Mutual Information Minimization Perspective—0
Deciphering and Optimizing Multi-Task Learning: a Random Matrix Approach—0
On the use of linguistic similarities to improve Neural Machine Translation for African Languages—0
CANVASEMB: Learning Layout Representation with Large-scale Pre-training for Graphic Design—0
Pseudo Label-Guided Multi Task Learning for Scene Understanding—0
Bayesian Context Aggregation for Neural Processes—0
Re-examining Routing Networks for Multi-task Learning—0
Reusing Preprocessing Data as Auxiliary Supervision in Conversational Analysis—0
Student Customized Knowledge Distillation: Bridging the Gap Between Student and Teacher—0
Task Switching Network for Multi-Task Learning—0
Unsupervised Task Clustering for Multi-Task Reinforcement LearningCode0
UserBERT: Self-supervised User Representation Learning—0
Variational Multi-Task Learning—0
Gated Ensemble of Spatio-temporal Mixture of Experts for Multi-task Learning in Ride-hailing System—0
Joint Air Quality and Weather Prediction Based on Multi-Adversarial Spatiotemporal Networks—0
Enhancing Handwritten Text Recognition with N-gram sequence decomposition and Multitask Learning—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