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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 1701–1725 of 3687 papers

TitleStatusHype
Federated Multi-Task Learning for THz Wideband Channel and DoA Estimation—0
Large-Scale Meta-Learning with Continual Trajectory Shifting—0
Anno-incomplete Multi-dataset Detection—0
Large-Scale Music Annotation and Retrieval: Learning to Rank in Joint Semantic Spaces—0
DFGET: Displacement-Field Assisted Graph Energy Transmitter for Gland Instance Segmentation—0
Latent Group Structured Multi-task Learning—0
Learning to Transfer via Modelling Multi-level Task Dependency—0
AutoSeM: Automatic Task Selection and Mixing in Multi-Task Learning—0
LaTeX-Numeric: Language-agnostic Text attribute eXtraction for E-commerce Numeric Attributes—0
LATEX-Numeric: Language Agnostic Text Attribute Extraction for Numeric Attributes—0
Federated Learning for Estimating Heterogeneous Treatment Effects—0
A Benchmark for Federated Hetero-Task Learning—0
Layer by Layer: Uncovering Where Multi-Task Learning Happens in Instruction-Tuned Large Language Models—0
Diabetic retinopathy image classification method based on GreenBen data augmentation—0
Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment—0
Collaborative Optimization in Financial Data Mining Through Deep Learning and ResNeXt—0
LEAF: A Benchmark for Federated Settings—0
Learnable Dependency-based Double Graph Structure for Aspect-based Sentiment Analysis—0
DiaNet: BERT and Hierarchical Attention Multi-Task Learning of Fine-Grained Dialect—0
Robust and flexible learning of a high-dimensional classification rule using auxiliary outcomes—0
Learning quantum properties from short-range correlations using multi-task networks—0
Learning an Interpretable Graph Structure in Multi-Task Learning—0
Learning Answer-Entailing Structures for Machine Comprehension—0
Differentiable Mask for Pruning Convolutional and Recurrent Networks—0
FedBone: Towards Large-Scale Federated 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