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Mixture-of-Experts

Papers

Showing 1251–1300 of 1312 papers

TitleStatusHype
Mixture of neural operator experts for learning boundary conditions and model selection—0
Mixture of Parrots: Experts improve memorization more than reasoning—0
Mixture of partially linear experts—0
Mixture of Quantized Experts (MoQE): Complementary Effect of Low-bit Quantization and Robustness—0
Mixture of Regression Experts in fMRI Encoding—0
Mixture of Routers—0
Mixture-of-Shape-Experts (MoSE): End-to-End Shape Dictionary Framework to Prompt SAM for Generalizable Medical Segmentation—0
Mixture of Tunable Experts - Behavior Modification of DeepSeek-R1 at Inference Time—0
Mixtures of Deep Neural Experts for Automated Speech Scoring—0
MJ-VIDEO: Fine-Grained Benchmarking and Rewarding Video Preferences in Video Generation—0
MM1.5: Methods, Analysis & Insights from Multimodal LLM Fine-tuning—0
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training—0
MMoE: Robust Spoiler Detection with Multi-modal Information and Domain-aware Mixture-of-Experts—0
μ-MoE: Test-Time Pruning as Micro-Grained Mixture-of-Experts—0
MoA: Mixture-of-Attention for Subject-Context Disentanglement in Personalized Image Generation—0
MobileFlow: A Multimodal LLM For Mobile GUI Agent—0
Mobile V-MoEs: Scaling Down Vision Transformers via Sparse Mixture-of-Experts—0
Mod-Adapter: Tuning-Free and Versatile Multi-concept Personalization via Modulation Adapter—0
MoDE: A Mixture-of-Experts Model with Mutual Distillation among the Experts—0
Model Agnostic Combination for Ensemble Learning—0
Beyond the Typical: Modeling Rare Plausible Patterns in Chemical Reactions by Leveraging Sequential Mixture-of-Experts—0
Modeling Task Relationships in Multi-variate Soft Sensor with Balanced Mixture-of-Experts—0
Model Merging in Pre-training of Large Language Models—0
Model Selection for Gaussian-gated Gaussian Mixture of Experts Using Dendrograms of Mixing Measures—0
Mod-Squad: Designing Mixture of Experts As Modular Multi-Task Learners—0
Mod-Squad: Designing Mixtures of Experts As Modular Multi-Task Learners—0
Modularity Matters: Learning Invariant Relational Reasoning Tasks—0
MoE-AMC: Enhancing Automatic Modulation Classification Performance Using Mixture-of-Experts—0
MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation—0
MoE-CAP: Benchmarking Cost, Accuracy and Performance of Sparse Mixture-of-Experts Systems—0
MoEC: Mixture of Expert Clusters—0
MoEC: Mixture of Experts Implicit Neural Compression—0
MoE-DiffIR: Task-customized Diffusion Priors for Universal Compressed Image Restoration—0
MoEfication: Conditional Computation of Transformer Models for Efficient Inference—0
MoE-GPS: Guidlines for Prediction Strategy for Dynamic Expert Duplication in MoE Load Balancing—0
MoE-Gyro: Self-Supervised Over-Range Reconstruction and Denoising for MEMS Gyroscopes—0
MoE-Lens: Towards the Hardware Limit of High-Throughput MoE LLM Serving Under Resource Constraints—0
MoE-Lightning: High-Throughput MoE Inference on Memory-constrained GPUs—0
MoE-Loco: Mixture of Experts for Multitask Locomotion—0
MoELoRA: Contrastive Learning Guided Mixture of Experts on Parameter-Efficient Fine-Tuning for Large Language Models—0
MoEMba: A Mamba-based Mixture of Experts for High-Density EMG-based Hand Gesture Recognition—0
MoEMoE: Question Guided Dense and Scalable Sparse Mixture-of-Expert for Multi-source Multi-modal Answering—0
MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks—0
MoE Parallel Folding: Heterogeneous Parallelism Mappings for Efficient Large-Scale MoE Model Training with Megatron Core—0
MoE-Pruner: Pruning Mixture-of-Experts Large Language Model using the Hints from Its Router—0
MoESD: Mixture of Experts Stable Diffusion to Mitigate Gender Bias—0
MoESD: Unveil Speculative Decoding's Potential for Accelerating Sparse MoE—0
MoE-SPNet: A Mixture-of-Experts Scene Parsing Network—0
MoET: Interpretable and Verifiable Reinforcement Learning via Mixture of Expert Trees—0
MoETuner: Optimized Mixture of Expert Serving with Balanced Expert Placement and Token Routing—0
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