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 1951–1975 of 3687 papers

TitleStatusHype
Short-term passenger flow prediction for multi-traffic modes: A Transformer and residual network based multi-task learning method—0
Sieg at MEDIQA 2019: Multi-task Neural Ensemble for Biomedical Inference and Entailment—0
Sign-regularized Multi-task Learning—0
SIMAC: A Semantic-Driven Integrated Multimodal Sensing And Communication Framework—0
Simple Compounded-Label Training for Fact Extraction and Verification—0
Simple Hierarchical Multi-Task Neural End-To-End Entity Linking for Biomedical Text—0
Simpler Does It: Generating Semantic Labels with Objectness Guidance—0
SimPose: Effectively Learning DensePose and Surface Normals of People from Simulated Data—0
SimPose: Effectively Learning DensePose and Surface Normals of People from Simulated Data—0
Sim-to-Real Optimization of Complex Real World Mobile Network with Imperfect Information via Deep Reinforcement Learning from Self-play—0
Simultaneous Estimation of X-ray Back-Scatter and Forward-Scatter using Multi-Task Learning—0
Simultaneous Modeling of Multiple Complications for Risk Profiling in Diabetes Care—0
Simultaneous or Sequential Training? How Speech Representations Cooperate in a Multi-Task Self-Supervised Learning System—0
Simultaneous Semantic and Collision Learning for 6-DoF Grasp Pose Estimation—0
Single-Input Multi-Output Model Merging: Leveraging Foundation Models for Dense Multi-Task Learning—0
Single Model for Influenza Forecasting of Multiple Countries by Multi-task Learning—0
Single-Stage Visual Relationship Learning using Conditional Queries—0
SIRe-Networks: Convolutional Neural Networks Architectural Extension for Information Preservation via Skip/Residual Connections and Interlaced Auto-Encoders—0
SJTU-NICT at MRP 2019: Multi-Task Learning for End-to-End Uniform Semantic Graph Parsing—0
SkillNet-NLG: General-Purpose Natural Language Generation with a Sparsely Activated Approach—0
SleepNet: Automated Sleep Analysis via Dense Convolutional Neural Network Using Physiological Time Series—0
Sliced Multi-Marginal Optimal Transport—0
SLiCK: Exploiting Subsequences for Length-Constrained Keyword Spotting—0
SLM as Guardian: Pioneering AI Safety with Small Language Models—0
Sluice Resolution without Hand-Crafted Features over Brittle Syntax Trees—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