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

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Showing 1151–1175 of 3687 papers

TitleStatusHype
Helping the Weak Makes You Strong: Simple Multi-Task Learning Improves Non-Autoregressive TranslatorsCode0
HeroNet: A Hybrid Retrieval-Generation Network for Conversational BotsCode0
HRNet: Differentially Private Hierarchical and Multi-Resolution Network for Human Mobility Data SynthesizationCode0
Imbalanced multi-label classification using multi-task learning with extractive summarizationCode0
ChangeMinds: Multi-task Framework for Detecting and Describing Changes in Remote SensingCode0
Evolutionary Multi-Task Injection Testing on Web Application FirewallsCode0
Co-evolutionary multi-task learning for dynamic time series predictionCode0
Is POS Tagging Necessary or Even Helpful for Neural Dependency Parsing?Code0
Learning Interpretable Microscopic Features of Tumor by Multi-task Adversarial CNNs To Improve GeneralizationCode0
Group Buying Recommendation Model Based on Multi-task LearningCode0
GYM at Qur’an QA 2023 Shared Task: Multi-Task Transfer Learning for Quranic Passage Retrieval and Question Answering with Large Language ModelsCode0
Fast Multiple Landmark Localisation Using a Patch-based Iterative NetworkCode0
Event Causality Identification via Generation of Important Context WordsCode0
Graph Star Net for Generalized Multi-Task LearningCode0
Graph-Induced Syntactic-Semantic Spaces in Transformer-Based Variational AutoEncodersCode0
Feature-oriented Deep Learning Framework for Pulmonary Cone-beam CT (CBCT) Enhancement with Multi-task Customized Perceptual LossCode0
Graph Neural Networks for Surfactant Multi-Property PredictionCode0
H2H: Heterogeneous Model to Heterogeneous System Mapping with Computation and Communication AwarenessCode0
Feature-weighted elastic net: using "features of features" for better predictionCode0
Graph-based Knowledge Distillation by Multi-head Attention NetworkCode0
Joint Training on Multiple Datasets With Inconsistent Labeling Criteria for Facial Expression RecognitionCode0
CeViT: Copula-Enhanced Vision Transformer in multi-task learning and bi-group image covariates with an application to myopia screeningCode0
ESM-NBR: fast and accurate nucleic acid-binding residue prediction via protein language model feature representation and multi-task learningCode0
KFC: Kinship Verification with Fair Contrastive Loss and Multi-Task LearningCode0
ERNIE 3.0 Tiny: Frustratingly Simple Method to Improve Task-Agnostic Distillation GeneralizationCode0
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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