{"total":20,"rows":[{"id":"2407.06204","title":"A Survey on Mixture of Experts in Large Language Models","created":"2024-06-26","cited_by_count":237,"area":"moe"},{"id":"2212.05055","title":"Sparse Upcycling: Training Mixture-of-Experts from Dense Checkpoints","created":"2022-12-09","cited_by_count":209,"area":"moe"},{"id":"2402.03226","title":"FuseMoE: Mixture-of-Experts Transformers for Fleximodal Fusion","created":"2024-02-05","cited_by_count":68,"area":"moe"},{"id":"2310.14188","title":"A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts","created":"2023-10-22","cited_by_count":23,"area":"moe"},{"id":"2402.02952","title":"On Least Square Estimation in Softmax Gating Mixture of Experts","created":"2024-02-05","cited_by_count":23,"area":"moe"},{"id":"2408.06793","title":"Layerwise Recurrent Router for Mixture-of-Experts","created":"2024-08-13","cited_by_count":21,"area":"moe"},{"id":"2410.02935","title":"On Expert Estimation in Hierarchical Mixture of Experts: Beyond Softmax Gating Functions","created":"2024-10-03","cited_by_count":16,"area":"moe"},{"id":"2401.13875","title":"Is Temperature Sample Efficient for Softmax Gaussian Mixture of Experts?","created":"2024-01-25","cited_by_count":15,"area":"moe"},{"id":"2504.00661","title":"DynMoLE: Boosting Mixture of LoRA Experts Fine-Tuning with a Hybrid Routing Mechanism","created":"2025-04-01","cited_by_count":11,"area":"moe"},{"id":"2402.16918","title":"m2mKD: Module-to-Module Knowledge Distillation for Modular Transformers","created":"2024-02-26","cited_by_count":5,"area":"moe"},{"id":"2411.08446","title":"LSH-MoE: Communication-efficient MoE Training via Locality-Sensitive Hashing","created":"2024-11-13","cited_by_count":5,"area":"moe"},{"id":"2503.03213","title":"Convergence Rates for Softmax Gating Mixture of Experts","created":"2025-03-05","cited_by_count":4,"area":"moe"},{"id":"2306.02824","title":"COMET: Learning Cardinality Constrained Mixture of Experts with Trees and Local Search","created":"2023-06-05","cited_by_count":2,"area":"moe"},{"id":"2409.14107","title":"Routing in Sparsely-gated Language Models responds to Context","created":"2024-09-21","cited_by_count":1,"area":"moe"},{"id":"2605.06665","title":"UniPool: A Globally Shared Expert Pool for Mixture-of-Experts","created":"2026-05-07","cited_by_count":1,"area":"moe"},{"id":"2605.25565","title":"RotMoLE: Enhancing Mixture of Low-Rank Experts through Rotational Gating Mechanism","created":"2026-05-25","cited_by_count":1,"area":"moe"},{"id":"2505.11785","title":"Improving Coverage in Combined Prediction Sets with Weighted p-values","created":"2025-05-17","cited_by_count":0,"area":"moe"},{"id":"2605.26776","title":"Towards Generalization-Oriented Models for Vehicle Routing Problems with Mixture-of-Experts","created":"2026-05-26","cited_by_count":0,"area":"moe"},{"id":"2606.14243","title":"Decoupled Mixture-of-Experts for Parametric Knowledge Injection","created":"2026-06-12","cited_by_count":0,"area":"moe"},{"id":"2609.35481","title":"TopoEP: Topology-Aware Load Balancing for Expert-Parallel MoE Training","created":"2026-09-28","cited_by_count":0,"area":"moe"}],"next_cursor":null}