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Multi-Task Learning
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Multi-task learning aims to learn multiple different tasks simultaneously while maximizing performance on one or all of the tasks.
<span style="color:grey; opacity: 0.6">( Image credit: Cross-stitch Networks for Multi-task Learning )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Mixpert: Mitigating Multimodal Learning Conflicts with Efficient Mixture-of-Vision-Experts
DeepChest: Dynamic Gradient-Free Task Weighting for Effective Multi-Task Learning in Chest X-ray Classification
CSI-Bench: A Large-Scale In-the-Wild Dataset for Multi-task WiFi Sensing
Risk-Sensitive Conformal Prediction for Catheter Placement Detection in Chest X-rays
MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning
Speech as a Multimodal Digital Phenotype for Multi-Task LLM-based Mental Health Prediction
Multi-Mode Process Control Using Multi-Task Inverse Reinforcement Learning
DeepMultiConnectome: Deep Multi-Task Prediction of Structural Connectomes Directly from Diffusion MRI Tractography
RetroMotion: Retrocausal Motion Forecasting Models are Instructable
Prot2Token: A Unified Framework for Protein Modeling via Next-Token Prediction
Multiple Wasserstein Gradient Descent Algorithm for Multi-Objective Distributional Optimization
HD-PiSSA: High-Rank Distributed Orthogonal Adaptation
NAN: A Training-Free Solution to Coefficient Estimation in Model Merging
Leveraging Unit Language Guidance to Advance Speech Modeling in Textless Speech-to-Speech Translation
Deep Learning Enabled Segmentation, Classification and Risk Assessment of Cervical Cancer
Transfer Learning from Visual Speech Recognition to Mouthing Recognition in German Sign Language
Multimodal Mixture of Low-Rank Experts for Sentiment Analysis and Emotion Recognition
Scalable Strategies for Continual Learning with Replay
Cross-Model Transfer of Task Vectors via Few-Shot Orthogonal Alignment
MCU: Improving Machine Unlearning through Mode Connectivity
The Ripple Effect: On Unforeseen Complications of Backdoor Attacks
Urban Representation Learning for Fine-grained Economic Mapping: A Semi-supervised Graph-based Approach
Uniform Loss vs. Specialized Optimization: A Comparative Analysis in Multi-Task Learning
Hierarchical Document Refinement for Long-context Retrieval-augmented Generation
Multimodal Assessment of Classroom Discourse Quality: A Text-Centered Attention-Based Multi-Task Learning Approach
CAT Merging: A Training-Free Approach for Resolving Conflicts in Model Merging
MultiTaskVIF: Segmentation-oriented visible and infrared image fusion via multi-task learning
Brain Hematoma Marker Recognition Using Multitask Learning: SwinTransformer and Swin-Unet
Leveraging Multi-Task Learning for Multi-Label Power System Security Assessment
MTL-UE: Learning to Learn Nothing for Multi-Task Learning
NN-Based Joint Mitigation of IQ Imbalance and PA Nonlinearity With Multiple States
RLMiniStyler: Light-weight RL Style Agent for Arbitrary Sequential Neural Style Generation
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian Manifolds
Measuring Hong Kong Massive Multi-Task Language Understanding
Multi-Scale Graph Learning for Anti-Sparse Downscaling
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