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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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1426–1450 of 3687 papers

TitleStatusHype
Adversarial Inductive Transfer Learning with input and output space adaptation—0
Domain Adversarial Training for Accented Speech Recognition—0
Domain Adversarial Neural Networks for Dysarthric Speech Recognition—0
Domain Adaptation of Recurrent Neural Networks for Natural Language Understanding—0
Benchmarking Joint Face Spoofing and Forgery Detection with Visual and Physiological Cues—0
A Multi-Task Learning Neural Network for Emotion-Cause Pair Extraction—0
Domain Adaptation for Deep Reinforcement Learning in Visually Distinct Games—0
Bench-Marking And Improving Arabic Automatic Image Captioning Through The Use Of Multi-Task Learning Paradigm—0
Does Multi-Task Learning Always Help?: An Evaluation on Health Informatics—0
Does Learning Specific Features for Related Parts Help Human Pose Estimation?—0
Behavior Self-Organization Supports Task Inference for Continual Robot Learning—0
A multi-task learning network using shared BERT models for aspect-based sentiment analysis—0
Adversarial Encoder-Multi-Task-Decoder for Multi-Stage Processes—0
A Convex Formulation for Learning Task Relationships in Multi-Task Learning—0
Document-Level Multi-Aspect Sentiment Classification as Machine Comprehension—0
Docking-based Virtual Screening with Multi-Task Learning—0
B-BACN: Bayesian Boundary-Aware Convolutional Network for Crack Characterization—0
A Multi-Task Learning Model for Super Resolution of Wireless Channel Characteristics—0
DLM-VMTL:A Double Layer Mapper for heterogeneous data video Multi-task prompt learning—0
DKE-Research at SemEval-2024 Task 2: Incorporating Data Augmentation with Generative Models and Biomedical Knowledge to Enhance Inference Robustness—0
Bayesian Optimization Augmented with Actively Elicited Expert Knowledge—0
A multi-task learning model for malware classification with useful file access pattern from API call sequence—0
Divide and Merge: Motion and Semantic Learning in End-to-End Autonomous Driving—0
Diversity and Depth in Per-Example Routing Models—0
Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data—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