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 1651–1675 of 3687 papers

TitleStatusHype
Keep Doing What Worked: Behavior Modelling Priors for Offline Reinforcement Learning—0
Keeping Consistency of Sentence Generation and Document Classification with Multi-Task Learning—0
Kernel-Based Learning for Smart Inverter Control—0
Kernel-based Multi-Task Contextual Bandits in Cellular Network Configuration—0
Fed-Focal Loss for imbalanced data classification in Federated Learning—0
Keyword Spotting for Hearing Assistive Devices Robust to External Speakers—0
DEPHN: Different Expression Parallel Heterogeneous Network using virtual gradient optimization for Multi-task Learning—0
K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning—0
K For The Price Of 1: Parameter Efficient Multi-task And Transfer Learning—0
Deploying Multi-task Online Server with Large Language Model—0
Dedge-AGMNet:an effective stereo matching network optimized by depth edge auxiliary task—0
Mixture of Latent Experts Using Tensor Products—0
Annotations Matter: Leveraging Multi-task Learning to Parse UD and SUD—0
Learning Multiple Tasks with Multilinear Relationship Networks—0
Knowledge Aware Emotion Recognition in Textual Conversations via Multi-Task Incremental Transformer—0
Knowledge Base Completion via Coupled Path Ranking—0
Learning Multiple Visual Tasks while Discovering their Structure—0
Learning Representation for Multitask learning through Self Supervised Auxiliary learning—0
Knowledge Efficient Deep Learning for Natural Language Processing—0
Design of Real-time Semantic Segmentation Decoder for Automated Driving—0
Learning from Synthetic Data: Facial Expression Classification based on Ensemble of Multi-task Networks—0
Knowledge-Interactive Network with Sentiment Polarity Intensity-Aware Multi-Task Learning for Emotion Recognition in Conversations—0
Knowledge transfer between bridges for drive-by monitoring using adversarial and multi-task learning—0
Learning Gaussian Maps for Dense Object Detection—0
Columbia at SemEval-2019 Task 7: Multi-task Learning for Stance Classification and Rumour Verification—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