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 1876–1900 of 3687 papers

TitleStatusHype
RSINet: Rotation-Scale Invariant Network for Online Visual Tracking—0
Rubik's Optical Neural Networks: Multi-task Learning with Physics-aware Rotation Architecture—0
Rugby-Bot: Utilizing Multi-Task Learning & Fine-Grained Features for Rugby League Analysis—0
Rumor Detection by Exploiting User Credibility Information, Attention and Multi-task Learning—0
Deep Safe Multi-Task Learning—0
Safe Screening Rules for Group OWL Models—0
SAM-CLIP: Merging Vision Foundation Models towards Semantic and Spatial Understanding—0
Same Representation, Different Attentions: Shareable Sentence Representation Learning from Multiple Tasks—0
SAQAM: Spatial Audio Quality Assessment Metric—0
SATformer: Transformer-Based UNSAT Core Learning—0
Scalable Attribution of Adversarial Attacks via Multi-Task Learning—0
Scalable Multi-Task Gaussian Process Tensor Regression for Normative Modeling of Structured Variation in Neuroimaging Data—0
Scalable Multi-Task Learning for Particle Collision Event Reconstruction with Heterogeneous Graph Neural Networks—0
Scalable Training of Trustworthy and Energy-Efficient Predictive Graph Foundation Models for Atomistic Materials Modeling: A Case Study with HydraGNN—0
Scalable Unidirectional Pareto Optimality for Multi-Task Learning with Constraints—0
Scalarization for Multi-Task and Multi-Domain Learning at Scale—0
Scale-aware Super-resolution Network with Dual Affinity Learning for Lesion Segmentation from Medical Images—0
Scale-specific auxiliary multi-task contrastive learning for deep liver vessel segmentation—0
Scaling End-to-End Models for Large-Scale Multilingual ASR—0
Scaling Multi-Domain Dialogue State Tracking via Query Reformulation—0
Scheduled Multi-Task Learning: From Syntax to Translation—0
Schema-Aware Multi-Task Learning for Complex Text-to-SQL—0
SC-LSTM: Learning Task-Specific Representations in Multi-Task Learning for Sequence Labeling—0
Seed Stocking Via Multi-Task Learning—0
Segmentation-grounded Scene Graph Generation—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