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 1851–1875 of 3687 papers

TitleStatusHype
Synthetic Photovoltaic and Wind Power Forecasting Data—0
Nowruz at SemEval-2022 Task 7: Tackling Cloze Tests with Transformers and Ordinal RegressionCode0
Pre-Training Transformer Decoder for End-to-End ASR Model with Unpaired Speech Data—0
Modular Adaptive Policy Selection for Multi-Task Imitation Learning through Task DivisionCode0
Multi-Task Learning for Visual Scene Understanding—0
Learning Optical Flow, Depth, and Scene Flow without Real-World Labels—0
Decoupled Multi-task Learning with Cyclical Self-Regulation for Face Parsing—0
Controllable Dynamic Multi-Task Architectures—0
Reinforcement Guided Multi-Task Learning Framework for Low-Resource Stereotype DetectionCode0
LibMTL: A Python Library for Multi-Task Learning—0
FedGradNorm: Personalized Federated Gradient-Normalized Multi-Task Learning—0
Multitask Emotion Recognition Model with Knowledge Distillation and Task Discriminator—0
Transformer-based Multimodal Information Fusion for Facial Expression Analysis—0
Utterance Rewriting with Contrastive Learning in Multi-turn Dialogue—0
A Computational Approach to Understand Mental Health from Reddit: Knowledge-aware Multitask Learning Framework—0
Reflective Fiber Faults Detection and Characterization Using Long-Short-Term Memory—0
To train or not to train adversarially: A study of bias mitigation strategies for speaker recognitionCode0
Feature-informed Latent Space Regularization for Music Source Separation—0
DeepAD: A Robust Deep Learning Model of Alzheimer's Disease Progression for Real-World Clinical Applications—0
Geographic Adaptation of Pretrained Language ModelsCode0
Zero-Shot Dependency Parsing with Worst-Case Aware Automated Curriculum LearningCode0
Choose Your QA Model Wisely: A Systematic Study of Generative and Extractive Readers for Question Answering—0
A Tree-Structured Multi-Task Model RecommenderCode0
A high-precision self-supervised monocular visual odometry in foggy weather based on robust cycled generative adversarial networks and multi-task learning aided depth estimation—0
A high-precision underwater object detection based on joint self-supervised deblurring and improved spatial transformer network—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