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 2676–2700 of 3687 papers

TitleStatusHype
Leveraging Code Generation to Improve Code Retrieval and Summarization via Dual Learning—0
Progressive Layered Extraction (PLE): A Novel Multi-Task Learning (MTL) Model for Personalized RecommendationsCode0
Multi-Branch Learning for Weakly-Labeled Sound Event Detection—0
The Sample Complexity of Meta Sparse Regression—0
Learning to Walk in the Real World with Minimal Human Effort—0
Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning—0
The Microsoft Toolkit of Multi-Task Deep Neural Networks for Natural Language Understanding—0
MILA: Multi-Task Learning from Videos via Efficient Inter-Frame Attention—0
Multi-Task Siamese Neural Network for Improving Replay Attack Detection—0
Speech-to-Singing Conversion in an Encoder-Decoder FrameworkCode1
Deeper Task-Specificity Improves Joint Entity and Relation ExtractionCode1
Speech Enhancement using Self-Adaptation and Multi-Head Self-Attention—0
Zero-Resource Cross-Domain Named Entity RecognitionCode1
SpotNet: Self-Attention Multi-Task Network for Object DetectionCode1
Deep Multi-Task Learning via Generalized Tensor Trace Norm—0
Deep Multi-Task Augmented Feature Learning via Hierarchical Graph Neural NetworkCode0
Salvaging Federated Learning by Local AdaptationCode1
A Simple General Approach to Balance Task Difficulty in Multi-Task Learning—0
Learning to Incorporate Structure Knowledge for Image InpaintingCode1
Deep Multi-task Multi-label CNN for Effective Facial Attribute Classification—0
Multi-Task Learning by a Top-Down Control Network—0
Analyzing Policy Distillation on Multi-Task Learning and Meta-Reinforcement Learning in Meta-World—0
Related Tasks can Share! A Multi-task Framework for Affective language—0
Self-supervised ECG Representation Learning for Emotion RecognitionCode1
Lane Detection in Low-light Conditions Using an Efficient Data Enhancement : Light Conditions Style TransferCode1
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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