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 3501–3525 of 3687 papers

TitleStatusHype
Patterns for Learning with Side InformationCode0
TaskWeb: Selecting Better Source Tasks for Multi-task NLPCode0
Direction-oriented Multi-objective Learning: Simple and Provable Stochastic AlgorithmsCode0
Federated Multi-Task Learning on Non-IID Data Silos: An Experimental StudyCode0
Multiple Instance Learning with Auxiliary Task Weighting for Multiple Myeloma ClassificationCode0
Multiple Wasserstein Gradient Descent Algorithm for Multi-Objective Distributional OptimizationCode0
Sequential Cross Attention Based Multi-task LearningCode0
Task-wise Split Gradient Boosting Trees for Multi-center Diabetes PredictionCode0
PD3: Better Low-Resource Cross-Lingual Transfer By Combining Direct Transfer and Annotation ProjectionCode0
Sequential Recommendation for Optimizing Both Immediate Feedback and Long-term RetentionCode0
A Multi-lingual Multi-task Architecture for Low-resource Sequence LabelingCode0
Dimension-reduced Optimization of Multi-zone Thermostatically Controlled LoadsCode0
Dancing in Chains: Reconciling Instruction Following and Faithfulness in Language ModelsCode0
CLMSM: A Multi-Task Learning Framework for Pre-training on Procedural TextCode0
Digital-twin-enhanced metal tube bending forming real-time prediction method based on Multi-source-input MTLCode0
Determining Question-Answer Plausibility in Crowdsourced Datasets Using Multi-Task LearningCode0
Multi-Task Accelerated MR Reconstruction Schemes for Jointly Training Multiple ContrastsCode0
Detecting semantic anomaliesCode0
Multi-task Active Learning for Pre-trained Transformer-based ModelsCode0
A Modulation Module for Multi-task Learning with Applications in Image RetrievalCode0
Multi-task Adversarial Learning for Semi-supervised Trajectory-User LinkingCode0
PENet: A Joint Panoptic Edge Detection NetworkCode0
AnywhereDoor: Multi-Target Backdoor Attacks on Object DetectionCode0
Perceptual Loss based Speech Denoising with an ensemble of Audio Pattern Recognition and Self-Supervised ModelsCode0
Federated 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