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 951–975 of 3687 papers

TitleStatusHype
A Role-Selected Sharing Network for Joint Machine-Human Chatting Handoff and Service Satisfaction AnalysisCode0
DYNASHARE: DYNAMIC NEURAL NETWORKS FOR MULTI-TASK LEARNINGCode0
Modular Universal Reparameterization: Deep Multi-task Learning Across Diverse DomainsCode0
On the Limitations of Sociodemographic Adaptation with TransformersCode0
HyperFace: A Deep Multi-task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender RecognitionCode0
Hyperparameter Auto-tuning in Self-Supervised Robotic LearningCode0
iCAR: Bridging Image Classification and Image-text Alignment for Visual RecognitionCode0
HTR-JAND: Handwritten Text Recognition with Joint Attention Network and Knowledge DistillationCode0
HRNet: Differentially Private Hierarchical and Multi-Resolution Network for Human Mobility Data SynthesizationCode0
Human Keypoint Detection by Progressive Context RefinementCode0
Patient-Specific Models of Treatment Effects Explain Heterogeneity in TuberculosisCode0
How does Multi-Task Training Affect Transformer In-Context Capabilities? Investigations with Function ClassesCode0
A Late-Stage Bitemporal Feature Fusion Network for Semantic Change DetectionCode0
PD3: Better Low-Resource Cross-Lingual Transfer By Combining Direct Transfer and Annotation ProjectionCode0
Hybrid Dual Mean-Teacher Network With Double-Uncertainty Guidance for Semi-Supervised Segmentation of MRI ScansCode0
Hierarchical Multi-task learning framework for Isometric-Speech Language TranslationCode0
Conv-MCD: A Plug-and-Play Multi-task Module for Medical Image SegmentationCode0
Effective Cross-Task Transfer Learning for Explainable Natural Language Inference with T5Code0
Convex Learning of Multiple Tasks and their StructureCode0
Bi-Preference Learning Heterogeneous Hypergraph Networks for Session-based RecommendationCode0
Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad CreativeCode0
Out-of-Scope Domain and Intent Classification through Hierarchical Joint ModelingCode0
Learning to Collaborate Over Graphs: A Selective Federated Multi-Task Learning ApproachCode0
Hybrid Losses for Hierarchical Embedding LearningCode0
HalluciNet-ing Spatiotemporal Representations Using a 2D-CNNCode0
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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