{"total":17,"rows":[{"id":"2401.06066","title":"DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models","created":"2024-01-11","cited_by_count":867,"area":"moe"},{"id":"2110.01786","title":"MoEfication: Transformer Feed-forward Layers are Mixtures of Experts","created":"2021-10-05","cited_by_count":152,"area":"moe"},{"id":"2601.07372","title":"Conditional Memory via Scalable Lookup: A New Axis of Sparsity for Large Language Models","created":"2026-01-12","cited_by_count":86,"area":"moe"},{"id":"2407.04153","title":"Mixture of A Million Experts","created":"2024-07-04","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":"2402.12851","title":"MoELoRA: Contrastive Learning Guided Mixture of Experts on Parameter-Efficient Fine-Tuning for Large Language Models","created":"2024-02-20","cited_by_count":56,"area":"moe"},{"id":"2405.19086","title":"MEMoE: Enhancing Model Editing with Mixture of Experts Adaptors","created":"2024-05-29","cited_by_count":9,"area":"moe"},{"id":"2601.08383","title":"Deconstructing Pre-training: Knowledge Attribution Analysis in MoE and Dense Models","created":"2026-01-13","cited_by_count":4,"area":"moe"},{"id":"2602.10965","title":"MoEEdit: Efficient and Routing-Stable Knowledge Editing for Mixture-of-Experts LLMs","created":"2026-02-11","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":"2505.21191","title":"Unveiling Instruction-Specific Neurons & Experts: An Analytical Framework for LLM's Instruction-Following Capabilities","created":"2025-05-27","cited_by_count":2,"area":"moe"},{"id":"2410.09687","title":"MoIN: Mixture of Introvert Experts to Upcycle an LLM","created":"2024-10-13","cited_by_count":0,"area":"moe"},{"id":"2501.06884","title":"Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning","created":"2025-01-12","cited_by_count":0,"area":"moe"},{"id":"2601.11977","title":"One-Shot Price Forecasting with Covariate-Guided Experts under Privacy Constraints","created":"2026-01-17","cited_by_count":0,"area":"moe"},{"id":"2605.24681","title":"Mix-MoE: Improving Multilingual Machine Translation of Large Language Models through Mixed MoEs","created":"2026-05-23","cited_by_count":0,"area":"moe"},{"id":"2607.24030","title":"MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition","created":"2026-07-27","cited_by_count":0,"area":"moe"},{"id":"2609.15126","title":"MoME: Mixture-of-Memory Embeddings for Context-Aware Sparse Lookup","created":"2026-09-14","cited_by_count":0,"area":"moe"}],"next_cursor":null}