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 3576–3600 of 3687 papers

TitleStatusHype
Federated Multi-Task Learning for THz Wideband Channel and DoA Estimation—0
Federated Multi-Objective Learning—0
Supervised Treebank Conversion: Data and Approaches—0
Entire Space Multi-Task Modeling via Post-Click Behavior Decomposition for Conversion Rate Prediction—0
Exploring Query Understanding for Amazon Product Search—0
Conversion of single-energy computed tomography to parametric maps of dual-energy computed tomography using convolutional neural network—0
Surpassing Human-Level Face Verification Performance on LFW with GaussianFace—0
SURREY-CTS-NLP at WASSA2022: An Experiment of Discourse and Sentiment Analysis for the Prediction of Empathy, Distress and Emotion—0
Fed-Focal Loss for imbalanced data classification in Federated Learning—0
FedGradNorm: Personalized Federated Gradient-Normalized Multi-Task Learning—0
Convergence rate of Bayesian tensor estimator: Optimal rate without restricted strong convexity—0
Visual Exemplar Driven Task-Prompting for Unified Perception in Autonomous Driving—0
FedNILM: Applying Federated Learning to NILM Applications at the Edge—0
Controllable Pareto Multi-Task Learning—0
FewFedWeight: Few-shot Federated Learning Framework across Multiple NLP Tasks—0
Few-Shot and Zero-Shot Learning for Historical Text Normalization—0
Domain-Agnostic Few-Shot Classification by Learning Disparate Modulators—0
Controllable Neural Architectures for Multi-Task Control—0
Few-shot Multi-Task Learning of Linear Invariant Features with Meta Subspace Pursuit—0
Few-Shot Multi-task Learning via Implicit regularization—0
Few-Shot Preference Learning for Human-in-the-Loop RL—0
Learning to Generate Prompts for Dialogue Generation through Reinforcement Learning—0
Few-shot Segmentation with Optimal Transport Matching and Message Flow—0
Controllable Dynamic Multi-Task Architectures—0
Survey on Large Language Model-Enhanced Reinforcement Learning: Concept, Taxonomy, and Methods—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