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 726–750 of 3687 papers

TitleStatusHype
Automatically Scoring Freshman Writing: A Preliminary Investigation—0
A Multi-task Learning Approach to Adapting Bilingual Word Embeddings for Cross-lingual Named Entity Recognition—0
Multi-target prediction for dummies using two-branch neural networks—0
A Dual-Decoder Conformer for Multilingual Speech Recognition—0
Personalized Multi-task Training for Recommender System—0
Distribution Conditional Denoising: A Flexible Discriminative Image Denoiser—0
Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Study—0
DKE-Research at SemEval-2024 Task 2: Incorporating Data Augmentation with Generative Models and Biomedical Knowledge to Enhance Inference Robustness—0
A Multi-task Learning Approach for Named Entity Recognition using Local Detection—0
Automated Heterogeneous Low-Bit Quantization of Multi-Model Deep Learning Inference Pipeline—0
Distributed Multi-Task Relationship Learning—0
Automated Essay Scoring Using Grammatical Variety and Errors with Multi-Task Learning and Item Response Theory—0
A Multi-Task Learning Approach for Meal Assessment—0
Distributed Networked Multi-task Learning—0
Autocorrect in the Process of Translation --- Multi-task Learning Improves Dialogue Machine Translation—0
A Multi-task Learning Approach for Improving Product Title Compression with User Search Log Data—0
A Distance Map Regularized CNN for Cardiac Cine MR Image Segmentation—0
A user-centric model of voting intention from Social Media—0
A Communication Theory Perspective on Prompting Engineering Methods for Large Language Models—0
Distributed Multi-Task Learning with Shared Representation—0
Distributed Primal-Dual Optimization for Online Multi-Task Learning—0
A Universal Framework for Inductive Transfer Parsing across Multi-typed Treebanks—0
A Unifying Framework for Typical Multi-Task Multiple Kernel Learning Problems—0
A Multitask Learning Approach for Diacritic Restoration—0
A Multi-Task Learning Algorithm for Non-personalized Recommendations—0
Show:102550
← PrevPage 30 of 148Next →
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