{"total":17,"rows":[{"id":"2112.10684","title":"Efficient Large Scale Language Modeling with Mixtures of Experts","created":"2021-12-20","cited_by_count":175,"area":"moe"},{"id":"2206.00277","title":"Task-Specific Expert Pruning for Sparse Mixture-of-Experts","created":"2022-06-01","cited_by_count":72,"area":"moe"},{"id":"2303.01610","title":"Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers","created":"2023-03-02","cited_by_count":59,"area":"moe"},{"id":"2206.04674","title":"Uni-Perceiver-MoE: Learning Sparse Generalist Models with Conditional MoEs","created":"2022-06-09","cited_by_count":58,"area":"moe"},{"id":"2107.11817","title":"Go Wider Instead of Deeper","created":"2021-07-25","cited_by_count":57,"area":"moe"},{"id":"2303.06318","title":"A Hybrid Tensor-Expert-Data Parallelism Approach to Optimize Mixture-of-Experts Training","created":"2023-03-11","cited_by_count":47,"area":"moe"},{"id":"2404.15045","title":"Multi-Head Mixture-of-Experts","created":"2024-04-23","cited_by_count":31,"area":"moe"},{"id":"2201.10890","title":"One Student Knows All Experts Know: From Sparse to Dense","created":"2022-01-26","cited_by_count":25,"area":"moe"},{"id":"2310.00811","title":"Sparse Backpropagation for MoE Training","created":"2023-10-01","cited_by_count":17,"area":"moe"},{"id":"2310.04361","title":"Exploiting Activation Sparsity with Dense to Dynamic-k Mixture-of-Experts Conversion","created":"2023-10-06","cited_by_count":16,"area":"moe"},{"id":"2207.09094","title":"MoEC: Mixture of Expert Clusters","created":"2022-07-19","cited_by_count":14,"area":"moe"},{"id":"2305.13999","title":"Towards A Unified View of Sparse Feed-Forward Network in Pretraining Large Language Model","created":"2023-05-23","cited_by_count":9,"area":"moe"},{"id":"2203.06850","title":"Efficient Language Modeling with Sparse all-MLP","created":"2022-03-14","cited_by_count":8,"area":"moe"},{"id":"2306.04845","title":"Mixture-of-Supernets: Improving Weight-Sharing Supernet Training with Architecture-Routed Mixture-of-Experts","created":"2023-06-08","cited_by_count":7,"area":"moe"},{"id":"2506.12417","title":"HarMoEny: Efficient Multi-GPU Inference of MoE Models","created":"2025-06-14","cited_by_count":7,"area":"moe"},{"id":"2503.11144","title":"MoLEx: Mixture of Layer Experts for Finetuning with Sparse Upcycling","created":"2025-03-14","cited_by_count":5,"area":"moe"},{"id":"2503.08467","title":"Accelerating MoE Model Inference with Expert Sharding","created":"2025-03-11","cited_by_count":0,"area":"moe"}],"next_cursor":null}