{"total":23,"rows":[{"id":"2405.14297","title":"Dynamic Mixture of Experts: An Auto-Tuning Approach for Efficient Transformer Models","created":"2024-05-23","cited_by_count":56,"area":"moe"},{"id":"2412.14219","title":"A Survey on Inference Optimization Techniques for Mixture of Experts Models","created":"2024-12-18","cited_by_count":47,"area":"moe"},{"id":"2508.01699","title":"TimeExpert: An Expert-Guided Video LLM for Video Temporal Grounding","created":"2025-08-03","cited_by_count":14,"area":"moe"},{"id":"2502.04416","title":"Analytical FFN-to-MoE Restructuring via Activation Pattern Analysis","created":"2025-02-06","cited_by_count":8,"area":"moe"},{"id":"2509.26520","title":"Training Matryoshka Mixture-of-Experts for Elastic Inference-Time Expert Utilization","created":"2025-09-30","cited_by_count":7,"area":"moe"},{"id":"2505.07260","title":"UMoE: Unifying Attention and FFN with Shared Experts","created":"2025-05-12","cited_by_count":6,"area":"moe"},{"id":"2410.16077","title":"CartesianMoE: Boosting Knowledge Sharing among Experts via Cartesian Product Routing in Mixture-of-Experts","created":"2024-10-21","cited_by_count":5,"area":"moe"},{"id":"2604.08133","title":"Alloc-MoE: Budget-Aware Expert Activation Allocation for Efficient Mixture-of-Experts Inference","created":"2026-04-09","cited_by_count":4,"area":"moe"},{"id":"2512.13996","title":"DTop-p MoE: Sparsity-Controlled Dynamic Top-p MoE for Foundation Model Pre-training","created":"2025-12-16","cited_by_count":3,"area":"moe"},{"id":"2603.11535","title":"Expert Threshold Routing for Autoregressive Language Modeling with Dynamic Computation Allocation and Load Balancing","created":"2026-03-12","cited_by_count":3,"area":"moe"},{"id":"2502.03884","title":"Rank Also Matters: Hierarchical Configuration for Mixture of Adapter Experts in LLM Fine-Tuning","created":"2025-02-06","cited_by_count":2,"area":"moe"},{"id":"2606.25821","title":"SARA: Unlocking Multilingual Knowledge in Mixture-of-Experts via Semantically Anchored Routing Alignment","created":"2026-06-24","cited_by_count":2,"area":"moe"},{"id":"2607.20426","title":"Knowledge Injection Exists in MoE? Exploring Expert-Aware Contrast Decoding in MoE for Mitigating LLMs'Hallucinations","created":"2026-05-08","cited_by_count":2,"area":"moe"},{"id":"2503.02495","title":"Union of Experts: Adapting Hierarchical Routing to Equivalently Decomposed Transformer","created":"2025-03-04","cited_by_count":1,"area":"moe"},{"id":"2605.14438","title":"BEAM: Binary Expert Activation Masking for Dynamic Routing in MoE","created":"2026-05-14","cited_by_count":1,"area":"moe"},{"id":"2606.29982","title":"Beyond Uniform Experts: Cost-Aware Expert Execution for Efficient Multi-Device MoE Inference","created":"2026-06-29","cited_by_count":1,"area":"moe"},{"id":"2504.20446","title":"FT-MoE: Sustainable-learning Mixture of Experts for Fault-Tolerant Computing","created":"2025-04-29","cited_by_count":0,"area":"moe"},{"id":"2512.16494","title":"PoseMoE: Mixture-of-Experts Network for Monocular 3D Human Pose Estimation","created":"2025-12-18","cited_by_count":0,"area":"moe"},{"id":"2605.02444","title":"M\\textsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation","created":"2026-05-04","cited_by_count":0,"area":"moe"},{"id":"2606.09885","title":"TENP: Trapezoidal Expert Neuron Pruning For Mixture-of-Experts","created":"2026-06-03","cited_by_count":0,"area":"moe"},{"id":"2609.22199","title":"Improving Parameter Utilization by Sharing Neural Experts Across Layers in Transformers","created":"2026-08-31","cited_by_count":0,"area":"moe"},{"id":"2609.33614","title":"EAT: Expert Account Tracker for Efficient MoE Inference","created":"2026-09-27","cited_by_count":0,"area":"moe"},{"id":"2610.19033","title":"How Many Ranks Does a Token Need? A Noise-Floor Squelch for Rank-One LoRA Experts","created":"2026-10-13","cited_by_count":0,"area":"moe"}],"next_cursor":null}