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 2476–2500 of 3687 papers

TitleStatusHype
Polymer Informatics with Multi-Task Learning—0
A Multi-task Two-stream Spatiotemporal Convolutional Neural Network for Convective Storm Nowcasting—0
Large-Scale End-to-End Multilingual Speech Recognition and Language Identification with Multi-Task LearningCode0
Byzantine Resilient Distributed Multi-Task LearningCode0
Multi-task Supervised Learning via Cross-learning—0
Speech enhancement aided end-to-end multi-task learning for voice activity detection—0
Perceptual Loss based Speech Denoising with an ensemble of Audio Pattern Recognition and Self-Supervised ModelsCode0
MAM: Masked Acoustic Modeling for End-to-End Speech-to-Text Translation—0
Precise High-Dimensional Asymptotics for Quantifying Heterogeneous Transfers—0
TMT: A Transformer-based Modal Translator for Improving Multimodal Sequence Representations in Audio Visual Scene-aware Dialog—0
A General Multi-Task Learning Framework to Leverage Text Data for Speech to Text Tasks—0
A Federated Learning Approach to Anomaly Detection in Smart Buildings—0
Adversarial Training for Code Retrieval with Question-Description Relevance RegularizationCode0
Predicting Chemical Properties using Self-Attention Multi-task Learning based on SMILES RepresentationCode0
Training Flexible Depth Model by Multi-Task Learning for Neural Machine Translation—0
Multi-task Learning of Negation and Speculation for Targeted Sentiment ClassificationCode0
Hyperparameter Auto-tuning in Self-Supervised Robotic LearningCode0
Decision Making Problems with Funnel Structure: A Multi-Task Learning Approach with Application to Email Marketing Campaigns—0
Aerodynamic Data Predictions Based on Multi-task Learning—0
Semi-Supervised Semantic Segmentation in Earth Observation: The MiniFrance Suite, Dataset Analysis and Multi-task Network Study—0
Response Selection for Multi-Party Conversations withDynamic Topic Tracking—0
Multi-Task Learning for Cross-Lingual Abstractive Summarization—0
A Generalized Zero-Shot Framework for Emotion Recognition from Body Gestures—0
Controllable Pareto Multi-Task Learning—0
Channel Type Recognition in Wireless Communications: A Deep Learning Approach—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