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 1901–1925 of 3687 papers

TitleStatusHype
Multi-task learning from fixed-wing UAV images for 2D/3D city modeling—0
YOLOP: You Only Look Once for Panoptic Driving PerceptionCode1
Multi-Task Self-Training for Learning General Representations—0
Outdoor Position Recovery from HeterogeneousTelco Cellular Data—0
Federated Multi-Task Learning under a Mixture of DistributionsCode1
A Dual-Decoder Conformer for Multilingual Speech Recognition—0
Multilingual Speech Recognition for Low-Resource Indian Languages using Multi-Task conformer—0
Personalised Federated Learning: A Combinational Approach—0
A Multi-Task Learning Framework for COVID-19 Monitoring and Prediction of PPE Demand in Community Health Centres—0
Few-shot Segmentation with Optimal Transport Matching and Message Flow—0
More for Less: Non-Intrusive Speech Quality Assessment with Limited Annotations—0
An Analysis Of Entire Space Multi-Task Models For Post-Click Conversion Prediction—0
DeepCVA: Automated Commit-level Vulnerability Assessment with Deep Multi-task LearningCode1
Multi-task learning for jersey number recognition in Ice Hockey—0
Task-wise Split Gradient Boosting Trees for Multi-center Diabetes PredictionCode0
An Effective System for Multi-format Information ExtractionCode1
MobIE: A German Dataset for Named Entity Recognition, Entity Linking and Relation Extraction in the Mobility DomainCode1
Bagging Supervised Autoencoder Classifier for Credit Scoring—0
Billion-Scale Pretraining with Vision Transformers for Multi-Task Visual Representations—0
Improving Single-Image Defocus Deblurring: How Dual-Pixel Images Help Through Multi-Task LearningCode1
Mining the Benefits of Two-stage and One-stage HOI DetectionCode1
ConvNets vs. Transformers: Whose Visual Representations are More Transferable?—0
How Self-Supervised Learning Can be Used for Fine-Grained Head Pose Estimation?—0
UniNet: A Unified Scene Understanding Network and Exploring Multi-Task Relationships through the Lens of Adversarial AttacksCode0
Explainable AI and susceptibility to adversarial attacks: a case study in classification of breast ultrasound images—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