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 1451–1475 of 3687 papers

TitleStatusHype
Evolutionary Multi-Task Injection Testing on Web Application FirewallsCode0
Surround-View Cameras based Holistic Visual Perception for Automated DrivingCode0
Video-Based Frame-Level Facial Analysis of Affective Behavior on Mobile Devices Using EfficientNets—0
Deep Neural Network for Blind Visual Quality Assessment of 4K Content—0
Deep Estimation of Speckle Statistics Parametric Images—0
Learning to Generate Prompts for Dialogue Generation through Reinforcement Learning—0
Learning Ego 3D Representation as Ray TracingCode1
Quantitative Stock Investment by Routing Uncertainty-Aware Trading Experts: A Multi-Task Learning Approach—0
An Analysis of Selection Bias Issue for Online Advertising—0
RAAT: Relation-Augmented Attention Transformer for Relation Modeling in Document-Level Event ExtractionCode1
A Benchmark for Federated Hetero-Task Learning—0
Reconsidering Learning Objectives in Unbiased Recommendation with Unobserved Confounders—0
PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence UnderstandingCode1
Stochastic Multiple Target Sampling Gradient DescentCode1
PETRv2: A Unified Framework for 3D Perception from Multi-Camera ImagesCode3
Learning Disentangled Representations for Counterfactual Regression via Mutual Information Minimization—0
Enhancing Relation Extraction via Adversarial Multi-task LearningCode0
RMT-Net: Reject-aware Multi-Task Network for Modeling Missing-not-at-random Data in Financial Credit Scoring—0
Principle of Relevant Information for Graph SparsificationCode0
FiLM-Ensemble: Probabilistic Deep Learning via Feature-wise Linear ModulationCode1
Compressed Hierarchical Representations for Multi-Task Learning and Task ClusteringCode0
Tackling Multiple Tasks with One Single Learning Framework—0
Automatic Expert Selection for Multi-Scenario and Multi-Task Search—0
Multi-Task Learning with Multi-Query Transformer for Dense PredictionCode1
Task-Agnostic Continual Reinforcement Learning: Gaining Insights and Overcoming ChallengesCode1
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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