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

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Showing 2301–2325 of 3687 papers

TitleStatusHype
Multi-task Learning for Human Settlement Extent Regression and Local Climate Zone Classification—0
Deep Learning for Automatic Quality Grading of Mangoes: Methods and Insights—0
Distributed Deep Reinforcement Learning: An Overview—0
Double Meta-Learning for Data Efficient Policy Optimization in Non-Stationary Environments—0
Classification by Attention: Scene Graph Classification with Prior Knowledge—0
Logically Consistent Loss for Visual Question Answering—0
Unifying Instance and Panoptic Segmentation with Dynamic Rank-1 Convolutions—0
Out-of-Task Training for Dialog State Tracking Models—0
UP-DETR: Unsupervised Pre-training for Object Detection with TransformersCode1
RSINet: Rotation-Scale Invariant Network for Online Visual Tracking—0
A Multi-Task Deep Learning Framework to Localize the Eloquent Cortex in Brain Tumor Patients Using Dynamic Functional Connectivity—0
Cluster-Specific Predictions with Multi-Task Gaussian ProcessesCode0
Multi-task single channel speech enhancement using speech presence probability as a secondary task training target—0
Improving Speech Enhancement Performance by Leveraging Contextual Broad Phonetic Class Information—0
Anomaly Detection in Video via Self-Supervised and Multi-Task LearningCode1
G-RCN: Optimizing the Gap between Classification and Localization Tasks for Object Detection—0
A Theoretical Perspective on Differentially Private Federated Multi-task Learning—0
Graph-Based Neural Network Models with Multiple Self-Supervised Auxiliary Tasks—0
Re-framing Incremental Deep Language Models for Dialogue Processing with Multi-task LearningCode0
Fed-Focal Loss for imbalanced data classification in Federated Learning—0
Identifying Depressive Symptoms from Tweets: Figurative Language Enabled Multitask Learning Framework—0
Robust and flexible learning of a high-dimensional classification rule using auxiliary outcomes—0
Joint predictions of multi-modal ride-hailing demands: a deep multi-task multigraph learning-based approach—0
UmBERTo-MTSA @ AcCompl-It: Improving Complexity and Acceptability Prediction with Multi-task Learning on Self-Supervised AnnotationsCode0
Determining Question-Answer Plausibility in Crowdsourced Datasets Using Multi-Task LearningCode0
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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