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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

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Showing 551–600 of 3687 papers

TitleStatusHype
Multi-Task Learning with User Preferences: Gradient Descent with Controlled Ascent in Pareto OptimizationCode1
Learning from Synthetic AnimalsCode1
Regularizing Deep Multi-Task Networks using Orthogonal GradientsCode1
CopyMTL: Copy Mechanism for Joint Extraction of Entities and Relations with Multi-Task LearningCode1
Forgetting to learn logic programsCode1
On the Detection of Digital Face ManipulationCode1
Encoding Visual Attributes in Capsules for Explainable Medical DiagnosesCode1
Multi-task Generative Adversarial Learning on Geometrical Shape Reconstruction from EEG Brain SignalsCode1
An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment AnalysisCode1
Emotion-Cause Pair Extraction: A New Task to Emotion Analysis in TextsCode1
CIF: Continuous Integrate-and-Fire for End-to-End Speech RecognitionCode1
RetinaFace: Single-stage Dense Face Localisation in the WildCode1
Large Scale Holistic Video UnderstandingCode1
What and How Well You Performed? A Multitask Learning Approach to Action Quality AssessmentCode1
Language Models are Unsupervised Multitask LearnersCode1
Peeking into the Future: Predicting Future Person Activities and Locations in VideosCode1
LEAF: A Benchmark for Federated SettingsCode1
Beyond expectation: Deep joint mean and quantile regression for spatio-temporal problemsCode1
CentralNet: a Multilayer Approach for Multimodal FusionCode1
How emotional are you? Neural Architectures for Emotion Intensity Prediction in MicroblogsCode1
End-to-End Multi-Task Learning with AttentionCode1
The ApolloScape Open Dataset for Autonomous Driving and its ApplicationCode1
Semantic Line Detection and Its ApplicationsCode1
Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and SemanticsCode1
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
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
Developing a High-performance Framework for Speech Emotion Recognition in Naturalistic Conditions Challenge for Emotional Attribute Prediction—0
Macro Graph of Experts for Billion-Scale Multi-Task Recommendation—0
A Study on Speech Assessment with Visual Cues—0
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
FLAIR-HUB: Large-scale Multimodal Dataset for Land Cover and Crop Mapping—0
Task-driven real-world super-resolution of document scans—0
Graph Neural Networks in Modern AI-aided Drug Discovery—0
IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G—0
A Framework for Controllable Multi-objective Learning with Annealed Stein Variational Hypernetworks—0
Distributional encoding for Gaussian process regression with qualitative inputs—0
Just a Scratch: Enhancing LLM Capabilities for Self-harm Detection through Intent Differentiation and Emoji Interpretation—0
An SCMA Receiver for 6G NTN based on Multi-Task Learning—0
A Learned Cost Model-based Cross-engine Optimizer for SQL Workloads—0
Towards Unified Modeling in Federated Multi-Task Learning via Subspace Decoupling—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