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Mixture-of-Experts

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Showing 551–600 of 1312 papers

TitleStatusHype
ECG-EmotionNet: Nested Mixture of Expert (NMoE) Adaptation of ECG-Foundation Model for Driver Emotion Recognition—0
Unify and Anchor: A Context-Aware Transformer for Cross-Domain Time Series Forecasting—0
DeRS: Towards Extremely Efficient Upcycled Mixture-of-Experts Models—0
Explainable Classifier for Malignant Lymphoma Subtyping via Cell Graph and Image Fusion—0
CL-MoE: Enhancing Multimodal Large Language Model with Dual Momentum Mixture-of-Experts for Continual Visual Question Answering—0
CoSMoEs: Compact Sparse Mixture of Experts—0
UniCodec: Unified Audio Codec with Single Domain-Adaptive Codebook—0
Mixture of Experts for Recognizing Depression from Interview and Reading Tasks—0
Mixture of Experts-augmented Deep Unfolding for Activity Detection in IRS-aided Systems—0
Drop-Upcycling: Training Sparse Mixture of Experts with Partial Re-initialization—0
OneRec: Unifying Retrieve and Rank with Generative Recommender and Iterative Preference Alignment—0
The Empirical Impact of Reducing Symmetries on the Performance of Deep Ensembles and MoE—0
Evaluating Expert Contributions in a MoE LLM for Quiz-Based Tasks—0
ENACT-Heart -- ENsemble-based Assessment Using CNN and Transformer on Heart Sounds—0
BigMac: A Communication-Efficient Mixture-of-Experts Model Structure for Fast Training and Inference—0
An Autonomous Network Orchestration Framework Integrating Large Language Models with Continual Reinforcement Learning—0
Binary-Integer-Programming Based Algorithm for Expert Load Balancing in Mixture-of-Experts ModelsCode0
Tight Clusters Make Specialized ExpertsCode0
Ray-Tracing for Conditionally Activated Neural Networks—0
Unraveling the Localized Latents: Learning Stratified Manifold Structures in LLM Embedding Space with Sparse Mixture-of-Experts—0
Every Expert Matters: Towards Effective Knowledge Distillation for Mixture-of-Experts Language Models—0
DSMoE: Matrix-Partitioned Experts with Dynamic Routing for Computation-Efficient Dense LLMs—0
How to Upscale Neural Networks with Scaling Law? A Survey and Practical Guidelines—0
Connector-S: A Survey of Connectors in Multi-modal Large Language Models—0
Fate: Fast Edge Inference of Mixture-of-Experts Models via Cross-Layer GateCode0
Mixture of Tunable Experts - Behavior Modification of DeepSeek-R1 at Inference Time—0
ClimateLLM: Efficient Weather Forecasting via Frequency-Aware Large Language Models—0
Probing Semantic Routing in Large Mixture-of-Expert Models—0
Eidetic Learning: an Efficient and Provable Solution to Catastrophic ForgettingCode0
Mixture of Decoupled Message Passing Experts with Entropy Constraint for General Node Classification—0
MoHAVE: Mixture of Hierarchical Audio-Visual Experts for Robust Speech Recognition—0
Memory Analysis on the Training Course of DeepSeek Models—0
MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks—0
MoETuner: Optimized Mixture of Expert Serving with Balanced Expert Placement and Token Routing—0
MoEMba: A Mamba-based Mixture of Experts for High-Density EMG-based Hand Gesture Recognition—0
Klotski: Efficient Mixture-of-Expert Inference via Expert-Aware Multi-Batch PipelineCode0
Mol-MoE: Training Preference-Guided Routers for Molecule GenerationCode0
fMoE: Fine-Grained Expert Offloading for Large Mixture-of-Experts Serving—0
Leveraging Pre-Trained Models for Multimodal Class-Incremental Learning under Adaptive Fusion—0
Towards Foundational Models for Dynamical System Reconstruction: Hierarchical Meta-Learning via Mixture of Experts—0
Joint MoE Scaling Laws: Mixture of Experts Can Be Memory Efficient—0
Mixture of neural operator experts for learning boundary conditions and model selection—0
Optimizing Robustness and Accuracy in Mixture of Experts: A Dual-Model Approach—0
ReGNet: Reciprocal Space-Aware Long-Range Modeling for Crystalline Property Prediction—0
Brief analysis of DeepSeek R1 and it's implications for Generative AI—0
M2R2: Mixture of Multi-Rate Residuals for Efficient Transformer Inference—0
MJ-VIDEO: Fine-Grained Benchmarking and Rewarding Video Preferences in Video Generation—0
CLIP-UP: A Simple and Efficient Mixture-of-Experts CLIP Training Recipe with Sparse Upcycling—0
MergeME: Model Merging Techniques for Homogeneous and Heterogeneous MoEs—0
Distribution-aware Fairness Learning in Medical Image Segmentation From A Control-Theoretic PerspectiveCode0
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