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 1551–1575 of 3687 papers

TitleStatusHype
Multi-target prediction for dummies using two-branch neural networks—0
A Multi-task Learning Approach to Adapting Bilingual Word Embeddings for Cross-lingual Named Entity Recognition—0
A Dual-Decoder Conformer for Multilingual Speech Recognition—0
A Comparison of Character Neural Language Model and Bootstrapping for Language Identification in Multilingual Noisy Texts—0
3D Virtual Garment Modeling from RGB Images—0
Dedge-AGMNet:an effective stereo matching network optimized by depth edge auxiliary task—0
Deploying Multi-task Online Server with Large Language Model—0
DEPHN: Different Expression Parallel Heterogeneous Network using virtual gradient optimization for Multi-task Learning—0
Dependent Multi-Task Learning with Causal Intervention for Image Captioning—0
Automated Heterogeneous Low-Bit Quantization of Multi-Model Deep Learning Inference Pipeline—0
A Multi-task Learning Approach for Named Entity Recognition using Local Detection—0
Dependency Parsing as Sequence Labeling with Head-Based Encoding and Multi-Task 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
Delving into 3D Action Anticipation from Streaming Videos—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
DELATOR: Money Laundering Detection via Multi-Task Learning on Large Transaction Graphs—0
A user-centric model of voting intention from Social Media—0
A Distance Map Regularized CNN for Cardiac Cine MR Image Segmentation—0
A Communication Theory Perspective on Prompting Engineering Methods for Large Language Models—0
Deep Task-specific Bottom Representation Network for Multi-Task Recommendation—0
A Universal Framework for Inductive Transfer Parsing across Multi-typed Treebanks—0
Deep Structured Output Learning for Unconstrained Text Recognition—0
Deep sparse multi-task learning for feature selection in Alzheimer’s disease diagnosis—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