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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 1–25 of 3687 papers

TitleStatusHype
SGCL: Unifying Self-Supervised and Supervised Learning for Graph Recommendation—0
Robust-Multi-Task Gradient BoostingCode0
SAMO: A Lightweight Sharpness-Aware Approach for Multi-Task Optimization with Joint Global-Local PerturbationCode0
Opportunistic Osteoporosis Diagnosis via Texture-Preserving Self-Supervision, Mixture of Experts and Multi-Task Integration—0
AnchorDP3: 3D Affordance Guided Sparse Diffusion Policy for Robotic Manipulation—0
An Audio-centric Multi-task Learning Framework for Streaming Ads Targeting on Spotify—0
SonicVerse: Multi-Task Learning for Music Feature-Informed CaptioningCode2
Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment—0
CALM: Consensus-Aware Localized Merging for Multi-Task LearningCode0
Training-free LLM Merging for Multi-task LearningCode0
Generative Representational Learning of Foundation Models for Recommendation—0
Macro Graph of Experts for Billion-Scale Multi-Task Recommendation—0
Developing a High-performance Framework for Speech Emotion Recognition in Naturalistic Conditions Challenge for Emotional Attribute Prediction—0
A Study on Speech Assessment with Visual Cues—0
Non-Contact Health Monitoring During Daily Personal Care RoutinesCode1
Learning to Collaborate Over Graphs: A Selective Federated Multi-Task Learning ApproachCode0
Merging Smarter, Generalizing Better: Enhancing Model Merging on OOD Data—0
Speaker-Distinguishable CTC: Learning Speaker Distinction Using CTC for Multi-Talker Speech Recognition—0
StableMTL: Repurposing Latent Diffusion Models for Multi-Task Learning from Partially Annotated Synthetic DatasetsCode1
FLAIR-HUB: Large-scale Multimodal Dataset for Land Cover and Crop Mapping—0
Task-driven real-world super-resolution of document scans—0
IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G—0
Graph Neural Networks in Modern AI-aided Drug Discovery—0
A Framework for Controllable Multi-objective Learning with Annealed Stein Variational Hypernetworks—0
An SCMA Receiver for 6G NTN based on Multi-Task Learning—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