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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 376–400 of 3687 papers

TitleStatusHype
Learning to Generate Semantic Layouts for Higher Text-Image Correspondence in Text-to-Image SynthesisCode1
Learning to Predict 3D Lane Shape and Camera Pose from a Single Image via Geometry ConstraintsCode1
Learning to Relate Depth and Semantics for Unsupervised Domain AdaptationCode1
A Multi-Head Ensemble Multi-Task Learning Approach for Dynamical Computation OffloadingCode1
Audio-Visual Deception Detection: DOLOS Dataset and Parameter-Efficient Crossmodal LearningCode1
Leveraging convergence behavior to balance conflicting tasks in multi-task learningCode1
Leveraging Language Representation for Material Recommendation, Ranking, and ExplorationCode1
Longitudinal Data and a Semantic Similarity Reward for Chest X-Ray Report GenerationCode1
Look\&Listen: Multi-Modal Correlation Learning for Active Speaker Detection and Speech EnhancementCode1
CTIN: Robust Contextual Transformer Network for Inertial NavigationCode1
M2GRL: A Multi-task Multi-view Graph Representation Learning Framework for Web-scale Recommender SystemsCode1
DeepUnifiedMom: Unified Time-series Momentum Portfolio Construction via Multi-Task Learning with Multi-Gate Mixture of ExpertsCode1
Many Hands Make Light Work: Using Essay Traits to Automatically Score EssaysCode1
MATINF: A Jointly Labeled Large-Scale Dataset for Classification, Question Answering and SummarizationCode1
An End-to-End Multi-Task Learning Model for Image-based Table RecognitionCode1
A Multi-Task Deep Learning Framework for Building Footprint SegmentationCode1
Beyond expectation: Deep joint mean and quantile regression for spatio-temporal problemsCode1
A Dependency Syntactic Knowledge Augmented Interactive Architecture for End-to-End Aspect-based Sentiment AnalysisCode1
MetaBEV: Solving Sensor Failures for BEV Detection and Map SegmentationCode1
A Frustratingly Easy Approach for Entity and Relation ExtractionCode1
Compressed Context Memory For Online Language Model InteractionCode1
CodeTrans: Towards Cracking the Language of Silicon's Code Through Self-Supervised Deep Learning and High Performance ComputingCode1
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and GenerationCode1
Combinatorial Optimization Perspective based Framework for Multi-behavior RecommendationCode1
Compressed Interaction Graph based Framework for Multi-behavior RecommendationCode1
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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