{"total":19,"rows":[{"id":"2409.16040","title":"Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts","created":"2024-09-24","cited_by_count":287,"area":"moe"},{"id":"2410.10469","title":"Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts","created":"2024-10-14","cited_by_count":95,"area":"moe"},{"id":"2509.25278","title":"MAESTRO : Adaptive Sparse Attention and Robust Learning for Multimodal Dynamic Time Series","created":"2025-09-29","cited_by_count":10,"area":"moe"},{"id":"2602.21693","title":"TiMi: Empower Time Series Transformers with Multimodal Mixture of Experts","created":"2026-02-25","cited_by_count":4,"area":"moe"},{"id":"2601.21641","title":"Seg-MoE: Multi-Resolution Segment-wise Mixture-of-Experts for Time Series Forecasting Transformers","created":"2026-01-29","cited_by_count":3,"area":"moe"},{"id":"2509.15105","title":"Super-Linear: A Lightweight Pretrained Mixture of Linear Experts for Time Series Forecasting","created":"2025-09-18","cited_by_count":2,"area":"moe"},{"id":"2509.22279","title":"Task-Aware Mixture-of-Experts for Time Series Analysis","created":"2025-09-26","cited_by_count":2,"area":"moe"},{"id":"2510.07459","title":"MoGU: Mixture-of-Gaussians with Uncertainty-based Gating for Time Series Forecasting","created":"2025-10-08","cited_by_count":2,"area":"moe"},{"id":"2508.07490","title":"N-BEATS-MOE: N-BEATS with a Mixture-of-Experts Layer for Heterogeneous Time Series Forecasting","created":"2025-08-10","cited_by_count":1,"area":"moe"},{"id":"2406.02969","title":"Filtered not Mixed: Stochastic Filtering-Based Online Gating for Mixture of Large Language Models","created":"2024-06-05","cited_by_count":0,"area":"moe"},{"id":"2510.23396","title":"EMTSF:Extraordinary Mixture of SOTA Models for Time Series Forecasting","created":"2025-10-27","cited_by_count":0,"area":"moe"},{"id":"2512.02061","title":"Ada-MoGE: Adaptive Mixture of Gaussian Expert Model for Time Series Forecasting","created":"2025-11-29","cited_by_count":0,"area":"moe"},{"id":"2601.21866","title":"MoHETS: Long-term Time Series Forecasting with Mixture-of-Heterogeneous-Experts","created":"2026-01-29","cited_by_count":0,"area":"moe"},{"id":"2605.20678","title":"Dynamic TMoE: A Drift-Aware Dynamic Mixture of Experts Framework for Non-Stationary Time Series Forecasting","created":"2026-05-20","cited_by_count":0,"area":"moe"},{"id":"2606.08896","title":"FAME: Forecastability-Aware Mixture of Experts for Heterogeneous Time Series Forecasting","created":"2026-06-08","cited_by_count":0,"area":"moe"},{"id":"2606.09907","title":"LongMoE: Longitudinal Multimodal Learning via Trajectory-Aware Mixture-of-Experts","created":"2026-06-06","cited_by_count":0,"area":"moe"},{"id":"2607.14510","title":"VLT: A Vision-Language-Time Series Multimodal Foundation Model for Industrial Intelligence","created":"2026-07-16","cited_by_count":0,"area":"moe"},{"id":"2609.15172","title":"STHMoE: Hypergraph-Enhanced Heterogeneous Dependency Coordination for LLM-Based Urban Traffic Data Forecasting","created":"2026-09-14","cited_by_count":0,"area":"moe"},{"id":"2610.19603","title":"Beyond Static Positional Encoding: Bayesian Time-aware Attention for Non-Stationary Long-term Time Series Forecasting","created":"2026-10-14","cited_by_count":0,"area":"moe"}],"next_cursor":null}