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Multi-Task Learning

2117 directly classified papers

Papers per year

Papers

Uni-Med: A Unified Medical Generalist Foundation Model For Multi-Task Learning Via Connector-MoE NIPS 2024
Towards a "Universal Translator" for Neural Dynamics at Single-Cell, Single-Spike Resolution NIPS 2024
Double-Layer Hybrid-Label Identification Feature Selection for Multi-View Multi-Label Learning AAAI 2024
Toward Efficient Inference for Mixture of Experts NIPS 2024
Pessimistic Off-Policy Multi-Objective Optimization AISTATS 2024
A Cross-View Hierarchical Graph Learning Hypernetwork for Skill Demand-Supply Joint Prediction AAAI 2024
Personalized Federated Learning with Mixture of Models for Adaptive Prediction and Model Fine-Tuning NIPS 2024
Panacea: Pareto Alignment via Preference Adaptation for LLMs NIPS 2024
Automated Label Unification for Multi-Dataset Semantic Segmentation with GNNs NIPS 2024
Speaker- and Text-Independent Estimation of Articulatory Movements and Phoneme Alignments from Speech INTERSPEECH 2024
Aligner²: Enhancing Joint Multiple Intent Detection and Slot Filling via Adjustive and Forced Cross-Task Alignment AAAI 2024
Value Kaleidoscope: Engaging AI with Pluralistic Human Values, Rights, and Duties AAAI 2024
Stochastic-Constrained Stochastic Optimization with Markovian Data JMLR 2024
HyCoRec: Hypergraph-Enhanced Multi-Preference Learning for Alleviating Matthew Effect in Conversational Recommendation ACL 2024
Initializing Services in Interactive ML Systems for Diverse Users NIPS 2024
DrFuse: Learning Disentangled Representation for Clinical Multi-Modal Fusion with Missing Modality and Modal Inconsistency AAAI 2024
Heterogeneity-Guided Client Sampling: Towards Fast and Efficient Non-IID Federated Learning NIPS 2024
Knowledge Composition using Task Vectors with Learned Anisotropic Scaling NIPS 2024
Discovering Creative Behaviors through DUPLEX: Diverse Universal Features for Policy Exploration NIPS 2024
Learning to Learn in Interactive Constraint Acquisition AAAI 2024
ViSTec: Video Modeling for Sports Technique Recognition and Tactical Analysis AAAI 2024
MoDE: A Mixture-of-Experts Model with Mutual Distillation among the Experts AAAI 2024
Relative Policy-Transition Optimization for Fast Policy Transfer AAAI 2024
Multi-Domain Recommendation to Attract Users via Domain Preference Modeling AAAI 2024
Kaleidoscope: Learnable Masks for Heterogeneous Multi-agent Reinforcement Learning NIPS 2024