New MoE-related work in application

[csyfjiang]

GaVaMoE: Gaussian-Variational Gated Mixture of Experts for Explainable Recommendation
https://arxiv.org/abs/2410.11841

[csyfjiang]

• Stereo-Talker: Audio-driven 3D Human Synthesis with Prior-Guided Mixture-of-Experts
• Stealing User Prompts from Mixture of Experts
• ProMoE: Fast MoE-based LLM Serving using Proactive Caching
• Efficient and Effective Weight-Ensembling Mixture of Experts for Multi-Task Model Merging
• Neural Experts: Mixture of Experts for Implicit Neural Representations
• Efficient Mixture-of-Expert for Video-based Driver State and Physiological Multi-task Estimation in Conditional Autonomous Driving
• Towards a Blockchain and Opportunistic Edge Driven Metaverse of Everything
• GUMBEL-NERF: Representing Unseen Objects as Part-Compositional Neural Radiance Fields
• LLMs Can Evolve Continually on Modality for X-Modal Reasoning
• DMT-HI: MOE-based Hyperbolic Interpretable Deep Manifold Transformation for Unspervised Dimensionality Reduction
• Hierarchical Mixture of Experts: Generalizable Learning for High-Level Synthesis
• Read-ME: Refactorizing LLMs as Router-Decoupled Mixture of Experts with System Co-Design
• Mixture of Parrots: Experts improve memorization more than reasoning
• Robust and Explainable Depression Identification from Speech Using Vowel-Based Ensemble Learning Approaches
• MiLoRA: Efficient Mixture of Low-Rank Adaptation for Large Language Models Fine-tuning
• ExpertFlow: Optimized Expert Activation and Token Allocation for Efficient Mixture-of-Experts Inference
• Optimizing Mixture-of-Experts Inference Time Combining Model Deployment and Communication Scheduling
• LMHaze: Intensity-aware Image Dehazing with a Large-scale Multi-intensity Real Haze Dataset
• CartesianMoE: Boosting Knowledge Sharing among Experts via Cartesian Product Routing in Mixture-of-Experts
• Generalizing Motion Planners with Mixture of Experts for Autonomous Driving
• ViMoE: An Empirical Study of Designing Vision Mixture-of-Experts
• Unveiling and Consulting Core Experts in Retrieval-Augmented MoE-based LLMs
• LoRA-IR: Taming Low-Rank Experts for Efficient All-in-One Image Restoration
• MENTOR: Mixture-of-Experts Network with Task-Oriented Perturbation for Visual Reinforcement Learning
• MomentumSMoE: Integrating Momentum into Sparse Mixture of Experts
• ST-MoE-BERT: A Spatial-Temporal Mixture-of-Experts Framework for Long-Term Cross-City Mobility Prediction
• MoR: Mixture of Ranks for Low-Rank Adaptation Tuning
• EPS-MoE: Expert Pipeline Scheduler for Cost-Efficient MoE Inference
• Transformer Layer Injection: A Novel Approach for Efficient Upscaling of Large Language Models
• Quadratic Gating Functions in Mixture of Experts: A Statistical Insight
• Your Mixture-of-Experts LLM Is Secretly an Embedding Model For Free
• Learning to Ground VLMs without Forgetting
• Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts
• HydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning