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 1476–1500 of 3687 papers

TitleStatusHype
Distill Knowledge in Multi-task Reinforcement Learning with Optimal-Transport Regularization—0
Distillation based Multi-task Learning: A Candidate Generation Model for Improving Reading Duration—0
Baidu Translate: Research and Products—0
Distantly Supervised Relation Extraction with Sentence Reconstruction and Knowledge Base Priors—0
Bag-of-Words Transfer: Non-Contextual Techniques for Multi-Task Learning—0
Distance Correlation Based Brain Functional Connectivity Estimation and Non-Convex Multi-Task Learning for Developmental fMRI Studies—0
Disjoint Multi-task Learning between Heterogeneous Human-centric Tasks—0
Bagging Supervised Autoencoder Classifier for Credit Scoring—0
Disentangling Representations through Multi-task Learning—0
Disentangled Representation for Age-Invariant Face Recognition: A Mutual Information Minimization Perspective—0
Backdoor Attacks against Image-to-Image Networks—0
A Multi-task Learning Framework for Product Ranking with BERT—0
Adversarial Analysis of Natural Language Inference Systems—0
Disentangled Latent Spaces Facilitate Data-Driven Auxiliary Learning—0
Disentangled Interleaving Variational Encoding—0
Discriminatory Transfer—0
Discriminative Feature Learning with Foreground Attention for Person Re-Identification—0
A Weighted Predict-and-Optimize Framework for Power System Operation Considering Varying Impacts of Uncertainty—0
Discovering Collaborative Signals for Next POI Recommendation with Iterative Seq2Graph Augmentation—0
Discourse-Aware Emotion Cause Extraction in Conversations—0
A Multi-task Learning Framework for Drone State Identification and Trajectory Prediction—0
Direct Preference Optimization-Enhanced Multi-Guided Diffusion Model for Traffic Scenario Generation—0
Directly Optimizing IoU for Bounding Box Localization—0
A Vanilla Multi-Task Framework for Dense Visual Prediction Solution to 1st VCL Challenge -- Multi-Task Robustness Track—0
Dining on Details: LLM-Guided Expert Networks for Fine-Grained Food Recognition—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