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

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Showing 1–10 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
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All datasetsQM9Cityscapes testNYUv2OMNIGLOTCelebAUTKFacewireframe dataset

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MGDA-UBError8.25—Unverified