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 1026–1050 of 3687 papers

TitleStatusHype
Joint tone mapping and denoising of thermal infrared images via multi-scale Retinex and multi-task learning—0
Multi-Task Structural Learning using Local Task Similarity induced Neuron Creation and RemovalCode0
MTC: A Multi-Task Model for Encrypted Network Traffic Classification Based on Transformer and 1D-CNNCode1
An Extensible Multimodal Multi-task Object Dataset with Materials—0
Ensemble Modeling with Contrastive Knowledge Distillation for Sequential RecommendationCode0
UCF: Uncovering Common Features for Generalizable Deepfake DetectionCode3
π-Tuning: Transferring Multimodal Foundation Models with Optimal Multi-task InterpolationCode1
Multi-Task Learning Regression via Convex Clustering—0
Curriculum Modeling the Dependence among Targets with Multi-task Learning for Financial Marketing—0
Lane Change Intention Recognition and Vehicle Status Prediction for Autonomous Vehicles—0
Sebis at SemEval-2023 Task 7: A Joint System for Natural Language Inference and Evidence Retrieval from Clinical Trial ReportsCode0
Rubik's Optical Neural Networks: Multi-task Learning with Physics-aware Rotation Architecture—0
Object Semantics Give Us the Depth We Need: Multi-task Approach to Aerial Depth Completion—0
A Multi-Task Approach to Robust Deep Reinforcement Learning for Resource AllocationCode0
Fast GraspNeXt: A Fast Self-Attention Neural Network Architecture for Multi-task Learning in Computer Vision Tasks for Robotic Grasping on the Edge—0
MetaBEV: Solving Sensor Failures for BEV Detection and Map SegmentationCode1
AutoTaskFormer: Searching Vision Transformers for Multi-task Learning—0
AdaMTL: Adaptive Input-dependent Inference for Efficient Multi-Task LearningCode0
AutoSTL: Automated Spatio-Temporal Multi-Task Learning—0
Magnitude Invariant Parametrizations Improve Hypernetwork LearningCode1
Directly Optimizing IoU for Bounding Box Localization—0
AdaTT: Adaptive Task-to-Task Fusion Network for Multitask Learning in RecommendationsCode1
iPINNs: Incremental learning for Physics-informed neural networks—0
RoboPianist: Dexterous Piano Playing with Deep Reinforcement LearningCode2
Gated Mechanism Enhanced Multi-Task Learning for Dialog Routing—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