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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 901–950 of 3687 papers

TitleStatusHype
Extracting Fractional Inspiratory Time from Electrocardiograms—0
Divide and Merge: Motion and Semantic Learning in End-to-End Autonomous Driving—0
DKE-Research at SemEval-2024 Task 2: Incorporating Data Augmentation with Generative Models and Biomedical Knowledge to Enhance Inference Robustness—0
DLM-VMTL:A Double Layer Mapper for heterogeneous data video Multi-task prompt learning—0
Audio-Visual Speech Inpainting with Deep Learning—0
A multi-task learning model for malware classification with useful file access pattern from API call sequence—0
Docking-based Virtual Screening with Multi-Task Learning—0
Deep Learning for Automatic Quality Grading of Mangoes: Methods and Insights—0
A Multi-Task Learning Model for Super Resolution of Wireless Channel Characteristics—0
Document-Level Multi-Aspect Sentiment Classification as Machine Comprehension—0
A Multi-modal and Multi-task Learning Method for Action Unit and Expression Recognition—0
Does Multi-Task Learning Always Help?: An Evaluation on Health Informatics—0
Deep Learning Enabled Segmentation, Classification and Risk Assessment of Cervical Cancer—0
Domain Adaptation for Deep Reinforcement Learning in Visually Distinct Games—0
Domain Adaptation of Recurrent Neural Networks for Natural Language Understanding—0
Domain Adversarial Neural Networks for Dysarthric Speech Recognition—0
Domain Adversarial Training for Accented Speech Recognition—0
A Multi-Task Learning Neural Network for Emotion-Cause Pair Extraction—0
Domain Generalization for In-Orbit 6D Pose Estimation—0
BERT-based Multi-Task Model for Country and Province Level Modern Standard Arabic and Dialectal Arabic Identification—0
BERT-based Multi-Task Model for Country and Province Level MSA and Dialectal Arabic Identification—0
Double Meta-Learning for Data Efficient Policy Optimization in Non-Stationary Environments—0
Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks—0
A Multi-Task, Multi-Modal Approach for Predicting Categorical and Dimensional Emotions—0
Driving Scene Perception Network: Real-time Joint Detection, Depth Estimation and Semantic Segmentation—0
Better Together: Using Multi-task Learning to Improve Feature Selection within Structural Datasets—0
Drugs Resistance Analysis from Scarce Health Records via Multi-task Graph Representation—0
Better Transfer Learning with Inferred Successor Maps—0
3D medical image segmentation with labeled and unlabeled data using autoencoders at the example of liver segmentation in CT images—0
A convex optimization formulation for multivariate regression—0
DSReg: Using Distant Supervision as a Regularizer—0
DT4ECG: A Dual-Task Learning Framework for ECG-Based Human Identity Recognition and Human Activity Detection—0
EvoSampling: A Granular Ball-based Evolutionary Hybrid Sampling with Knowledge Transfer for Imbalanced Learning—0
Dual-Attention Frequency Fusion at Multi-Scale for Joint Segmentation and Deformable Medical Image Registration—0
Exceeding the Limits of Visual-Linguistic Multi-Task Learning—0
Exploiting Source-side Monolingual Data in Neural Machine Translation—0
Extractive Summarization of Legal Decisions using Multi-task Learning and Maximal Marginal Relevance—0
DUET: Detection Utilizing Enhancement for Text in Scanned or Captured Documents—0
DUT-NLP at MEDIQA 2019: An Adversarial Multi-Task Network to Jointly Model Recognizing Question Entailment and Question Answering—0
A Semi-Self-Supervised Approach for Dense-Pattern Video Object Segmentation—0
Dynamic Adaptive Optimization for Effective Sentiment Analysis Fine-Tuning on Large Language Models—0
Dynamic Adjustment of Matching Radii under the Broadcasting Mode: A Novel Multitask Learning Strategy and Temporal Modeling Approach—0
FewFedWeight: Few-shot Federated Learning Framework across Multiple NLP Tasks—0
Dynamically Updating Event Representations for Temporal Relation Classification with Multi-category Learning—0
Beyond without Forgetting: Multi-Task Learning for Classification with Disjoint Datasets—0
Dynamic Multi-Level Multi-Task Learning for Sentence Simplification—0
Deep Learning based Positioning with Multi-task Learning and Uncertainty-based Fusion—0
Deep Learning Approach for Matrix Completion Using Manifold Learning—0
Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks—0
Deep Latent Emotion Network for Multi-Task Learning—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