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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 351–375 of 3687 papers

TitleStatusHype
Beyond Relevance: Improving User Engagement by Personalization for Short-Video Search—0
GINTRIP: Interpretable Temporal Graph Regression using Information bottleneck and Prototype-based methodCode0
A Physics Informed Neural Network (PINN) Methodology for Coupled Moving Boundary PDEsCode0
A Literature Review of Keyword Spotting Technologies for Urdu—0
Human Insights Driven Latent Space for Different Driving Perspectives: A Unified Encoder for Efficient Multi-Task Inference—0
Acquiring Pronunciation Knowledge from Transcribed Speech Audio via Multi-task Learning—0
Self-supervised Multimodal Speech Representations for the Assessment of Schizophrenia Symptoms—0
REG: Refined Generalized Focal Loss for Road Asset Detection on Thai Highways Using Vision-Based Detection and Segmentation ModelsCode0
Spoofing-Aware Speaker Verification Robust Against Domain and Channel Mismatches—0
Static for Dynamic: Towards a Deeper Understanding of Dynamic Facial Expressions Using Static Expression DataCode1
MTLSO: A Multi-Task Learning Approach for Logic Synthesis Optimization—0
SLiCK: Exploiting Subsequences for Length-Constrained Keyword Spotting—0
SpinMultiNet: Neural Network Potential Incorporating Spin Degrees of Freedom with Multi-Task Learning—0
Tissue Concepts: supervised foundation models in computational pathologyCode2
A Key-Driven Framework for Identity-Preserving Face Anonymization—0
LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorchCode2
Few-shot Multi-Task Learning of Linear Invariant Features with Meta Subspace Pursuit—0
A Fashion Item Recommendation Model in Hyperbolic Space—0
TRACE: Transformer-based user Representations from Attributed Clickstream Event sequences—0
Real-time Accident Anticipation for Autonomous Driving Through Monocular Depth-Enhanced 3D Modeling—0
Efficient Multi-task Prompt Tuning for Recommendation—0
Theoretical Insights into Overparameterized Models in Multi-Task and Replay-Based Continual LearningCode0
DLM-VMTL:A Double Layer Mapper for heterogeneous data video Multi-task prompt learning—0
Anno-incomplete Multi-dataset Detection—0
An Exploratory Deep Learning Approach for Predicting Subsequent Suicidal Acts in Chinese Psychological Support HotlinesCode0
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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