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 3051–3075 of 3687 papers

TitleStatusHype
Veritatem Dies Aperit- Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding ApproachCode0
Predicting Multiple Demographic Attributes with Task Specific Embedding Transformation and Attention NetworkCode0
Towards automatic construction of multi-network models for heterogeneous multi-task learning—0
Multi-Task Time Series Analysis applied to Drug Response Modelling—0
Deep Octonion Networks—0
Natural Language Generation at Scale: A Case Study for Open Domain Question Answering—0
MUSEFood: Multi-sensor-based Food Volume Estimation on SmartphonesCode0
Knowledge-aware Complementary Product Representation Learning—0
Imbalanced multi-label classification using multi-task learning with extractive summarizationCode0
Few-Shot and Zero-Shot Learning for Historical Text Normalization—0
Scaling Multi-Domain Dialogue State Tracking via Query Reformulation—0
Practical Semantic Parsing for Spoken Language Understanding—0
SleepNet: Automated Sleep Analysis via Dense Convolutional Neural Network Using Physiological Time Series—0
Deep CNN-based Multi-task Learning for Open-Set RecognitionCode0
Representative Task Self-selection for Flexible Clustered Lifelong Learning—0
EdgeStereo: An Effective Multi-Task Learning Network for Stereo Matching and Edge Detection—0
Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled DataCode0
Better, Faster, Stronger Sequence Tagging Constituent ParsersCode0
FaceLiveNet+: A Holistic Networks For Face Authentication Based On Dynamic Multi-task Convolutional Neural Networks—0
Learning to Generate Questions by Learning What not to Generate—0
Multi-Task Learning with Contextualized Word Representations for Extented Named Entity Recognition—0
Language Models are Unsupervised Multitask LearnersCode1
SHEAR-net: An End-to-End Deep Learning Approach for Single Push Ultrasound Shear Wave Elasticity Imaging—0
Peeking into the Future: Predicting Future Person Activities and Locations in VideosCode1
Multi-task Learning for Target-dependent Sentiment ClassificationCode0
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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