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 2001–2025 of 3687 papers

TitleStatusHype
Three Birds with One Stone: Multi-Task Temporal Action Detection via Recycling Temporal Annotations—0
Polygonal Building Extraction by Frame Field LearningCode1
Enhancing Question Generation with Commonsense Knowledge—0
Practical Transferability Estimation for Image Classification Tasks—0
Multi-Task Learning for User Engagement and Adoption in Live Video Streaming EventsCode0
Unsupervised Domain Adaptation for Dysarthric Speech Detection via Domain Adversarial Training and Mutual Information Minimization—0
Multi-Task Learning and Adapted Knowledge Models for Emotion-Cause Extraction—0
Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective AdaptationCode1
Minimizing Communication while Maximizing Performance in Multi-Agent Reinforcement Learning—0
E2E-based Multi-task Learning Approach to Joint Speech and Accent Recognition—0
Interpretable Self-supervised Multi-task Learning for COVID-19 Information Retrieval and Extraction—0
Multi-script Handwritten Digit Recognition Using Multi-task Learning—0
Poisoning Deep Reinforcement Learning Agents with In-Distribution Triggers—0
HistoTransfer: Understanding Transfer Learning for Histopathology—0
Anomalous Sound Detection Using a Binary Classification Model and Class Centroids—0
Nested and Balanced Entity Recognition using Multi-Task Learning—0
Meta-Adaptive Nonlinear Control: Theory and AlgorithmsCode1
Instance-Level Task Parameters: A Robust Multi-task Weighting Framework—0
TASK AWARE MULTI-TASK LEARNING FOR SPEECH TO TEXT TASKS—0
A Semi-supervised Multi-task Learning Approach to Classify Customer Contact Intents—0
DUET: Detection Utilizing Enhancement for Text in Scanned or Captured Documents—0
Thompson Sampling with a Mixture Prior—0
Salient Object Ranking with Position-Preserved AttentionCode1
One Semantic Parser to Parse Them All: Sequence to Sequence Multi-Task Learning on Semantic Parsing Datasets—0
Parameter-efficient Multi-task Fine-tuning for Transformers via Shared HypernetworksCode1
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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