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 2226–2250 of 3687 papers

TitleStatusHype
LATEX-Numeric: Language Agnostic Text Attribute Extraction for Numeric Attributes—0
Autocorrect in the Process of Translation --- Multi-task Learning Improves Dialogue Machine Translation—0
Bridging Resolution: Making Sense of the State of the Art—0
Training ELECTRA Augmented with Multi-word Selection—0
Defending Pre-trained Language Models from Adversarial Word Substitutions Without Performance SacrificeCode0
Spatio-Temporal Dual Graph Neural Networks for Travel Time Estimation—0
Efficient and robust multi-task learning in the brain with modular latent primitives—0
Clustered Federated Learning via Generalized Total Variation MinimizationCode0
Multi-Task Learning of Generation and Classification for Emotion-Aware Dialogue Response Generation—0
Abusive Language Detection in Heterogeneous Contexts: Dataset Collection and the Role of Supervised AttentionCode0
De-identification of Privacy-related Entities in Job PostingsCode0
DaN+: Danish Nested Named Entities and Lexical NormalizationCode0
RotoGrad: Gradient Homogenization in Multi-Task Learning—0
Puck localization and multi-task event recognition in broadcast hockey videos—0
Non-contact Pain Recognition from Video Sequences with Remote Physiological Measurements Prediction—0
Dependent Multi-Task Learning with Causal Intervention for Image Captioning—0
Graph Neural Networks for Knowledge Enhanced Visual Representation of Paintings—0
Deep Multistage Multi-Task Learning for Quality Prediction of Multistage Manufacturing Systems—0
MUSER: MUltimodal Stress Detection using Emotion Recognition as an Auxiliary Task—0
Using Self-Supervised Auxiliary Tasks to Improve Fine-Grained Facial Representation—0
Stable and Effective One-Step Method for Person Search—0
OCHADAI-KYOTO at SemEval-2021 Task 1: Enhancing Model Generalization and Robustness for Lexical Complexity Prediction—0
Development of a Multi-Task Learning V-Net for Pulmonary Lobar Segmentation on Computed Tomography and Application to Diseased Lungs—0
Differentially Private Transferrable Deep Learning with Membership-Mappings—0
Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Study—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