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 3151–3175 of 3687 papers

TitleStatusHype
DEEP: DEnoising Entity Pre-training for Neural Machine Translation—0
DeepDistance: A Multi-task Deep Regression Model for Cell Detection in Inverted Microscopy Images—0
Deep Elastic Networks with Model Selection for Multi-Task Learning—0
DCRNN: A Deep Cross approach based on RNN for Partial Parameter Sharing in Multi-task Learning—0
Deep Estimation of Speckle Statistics Parametric Images—0
DeepFaceLIFT: Interpretable Personalized Models for Automatic Estimation of Self-Reported Pain—0
Data-Driven Fairness Generalization for Deepfake Detection—0
Deepfake Detection via Knowledge Injection—0
Spatio-Temporal Multi-Task Learning Transformer for Joint Moving Object Detection and Segmentation—0
DeepGeneMD: A Joint Deep Learning Model for Extracting Gene Mutation-Disease Knowledge from PubMed Literature—0
Deep generative model-driven multimodal prostate segmentation in radiotherapy—0
DeepHider: A Covert NLP Watermarking Framework Based on Multi-task Learning—0
DCMT: A Direct Entire-Space Causal Multi-Task Framework for Post-Click Conversion Estimation—0
Deep Joint Source-Channel Coding for Multi-Task Network—0
Deep Latent Emotion Network for Multi-Task Learning—0
Deep Learning Approach for Matrix Completion Using Manifold Learning—0
Deep Learning based Positioning with Multi-task Learning and Uncertainty-based Fusion—0
Deep Learning Enabled Segmentation, Classification and Risk Assessment of Cervical Cancer—0
DCCRN-KWS: an audio bias based model for noise robust small-footprint keyword spotting—0
Deep Learning for Automatic Quality Grading of Mangoes: Methods and Insights—0
Large-scale Causal Approaches to Debiasing Post-click Conversion Rate Estimation with Multi-task Learning—0
Deeply Learned Attributes for Crowded Scene Understanding—0
Deep Mixture of Diverse Experts for Large-Scale Visual Recognition—0
DCAN: Deep Contour-Aware Networks for Accurate Gland Segmentation—0
Data Sharing without Rewards in Multi-Task Offline Reinforcement Learning—0
Show:102550
← PrevPage 127 of 148Next →
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