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

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Showing 2851–2875 of 3687 papers

TitleStatusHype
Semantic Structure Extraction for Spreadsheet Tables with a Multi-task Learning Architecture—0
Progression Modelling for Online and Early Gesture DetectionCode0
Adaptive Scheduling for Multi-Task Learning—0
Neural Correction Model for Open-Domain Named Entity RecognitionCode0
Encoding Visual Attributes in Capsules for Explainable Medical DiagnosesCode1
Multitask Classification and Segmentation for Cancer Diagnosis in Mammography—0
Domain-Agnostic Few-Shot Classification by Learning Disparate Modulators—0
Deep Elastic Networks with Model Selection for Multi-Task Learning—0
Semi-supervised Vector-valued Learning: Improved Bounds and AlgorithmsCode0
Differentiable Mask for Pruning Convolutional and Recurrent Networks—0
Joint Learning of Saliency Detection and Weakly Supervised Semantic SegmentationCode0
Auxiliary Learning for Deep Multi-task Learning—0
Specializing Unsupervised Pretraining Models for Word-Level Semantic SimilarityCode0
Different Absorption from the Same Sharing: Sifted Multi-task Learning for Fake News Detection—0
Lexicon information in neural sentiment analysis: a multi-task learning approachCode0
Text-Based Joint Prediction of Numeric and Categorical Attributes of Entities in Knowledge Bases—0
Leveraging Non-Conversational Tasks for Low Resource Slot Filling: Does it help?—0
Multi-Task Learning of System Dialogue Act Selection for Supervised Pretraining of Goal-Oriented Dialogue Policies—0
NCLS: Neural Cross-Lingual SummarizationCode0
Multi-Task Learning with Language Modeling for Question Generation—0
DeepDistance: A Multi-task Deep Regression Model for Cell Detection in Inverted Microscopy Images—0
Metric-based Regularization and Temporal Ensemble for Multi-task Learning using Heterogeneous Unsupervised Tasks—0
Transfer Learning from Partial Annotations for Whole Brain Segmentation—0
Investigating Meta-Learning Algorithms for Low-Resource Natural Language Understanding Tasks—0
Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels—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