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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.
SGCL: Unifying Self-Supervised and Supervised Learning for Graph Recommendation
Robust-Multi-Task Gradient Boosting
SAMO: A Lightweight Sharpness-Aware Approach for Multi-Task Optimization with Joint Global-Local Perturbation
DuET: Dual Incremental Object Detection via Exemplar-Free Task Arithmetic
Opportunistic Osteoporosis Diagnosis via Texture-Preserving Self-Supervision, Mixture of Experts and Multi-Task Integration
AnchorDP3: 3D Affordance Guided Sparse Diffusion Policy for Robotic Manipulation
An Audio-centric Multi-task Learning Framework for Streaming Ads Targeting on Spotify
CultureMERT: Continual Pre-Training for Cross-Cultural Music Representation Learning
Subspace-Boosted Model Merging
SonicVerse: Multi-Task Learning for Music Feature-Informed Captioning
Leader360V: The Large-scale, Real-world 360 Video Dataset for Multi-task Learning in Diverse Environment
CALM: Consensus-Aware Localized Merging for Multi-Task Learning
Training-free LLM Merging for Multi-task Learning
Generative Representational Learning of Foundation Models for Recommendation
Macro Graph of Experts for Billion-Scale Multi-Task Recommendation
Developing a High-performance Framework for Speech Emotion Recognition in Naturalistic Conditions Challenge for Emotional Attribute Prediction
A Study on Speech Assessment with Visual Cues
Non-Contact Health Monitoring During Daily Personal Care Routines
Learning to Collaborate Over Graphs: A Selective Federated Multi-Task Learning Approach
Merging Smarter, Generalizing Better: Enhancing Model Merging on OOD Data
Speaker-Distinguishable CTC: Learning Speaker Distinction Using CTC for Multi-Talker Speech Recognition
StableMTL: Repurposing Latent Diffusion Models for Multi-Task Learning from Partially Annotated Synthetic Datasets
Task-driven real-world super-resolution of document scans
FLAIR-HUB: Large-scale Multimodal Dataset for Land Cover and Crop Mapping
A Framework for Controllable Multi-objective Learning with Annealed Stein Variational Hypernetworks
IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G
Graph Neural Networks in Modern AI-aided Drug Discovery
Distributional encoding for Gaussian process regression with qualitative inputs
Just a Scratch: Enhancing LLM Capabilities for Self-harm Detection through Intent Differentiation and Emoji Interpretation
An SCMA Receiver for 6G NTN based on Multi-Task Learning
A Learned Cost Model-based Cross-engine Optimizer for SQL Workloads
FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA
Towards Unified Modeling in Federated Multi-Task Learning via Subspace Decoupling
On Fairness of Task Arithmetic: The Role of Task Vectors
Multi-task Learning for Heterogeneous Data via Integrating Shared and Task-Specific Encodings
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