ST-MoE-BERT: A Spatial-Temporal Mixture-of-Experts Framework for Long-Term Cross-City Mobility Prediction
Fuente:
arXiv
Guardado en:
| Autores principales: | He, Haoyu, Luo, Haozheng, Wang, Qi R. |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
RHYTHM: Reasoning with Hierarchical Temporal Tokenization for Human Mobility
por: He, Haoyu, et al.
Publicado: (2025)
por: He, Haoyu, et al.
Publicado: (2025)
Mixture of Experts (MoE): A Big Data Perspective
por: Gan, Wensheng, et al.
Publicado: (2025)
por: Gan, Wensheng, et al.
Publicado: (2025)
MoE-Health: A Mixture of Experts Framework for Robust Multimodal Healthcare Prediction
por: Wang, Xiaoyang, et al.
Publicado: (2025)
por: Wang, Xiaoyang, et al.
Publicado: (2025)
MoE++: Accelerating Mixture-of-Experts Methods with Zero-Computation Experts
por: Jin, Peng, et al.
Publicado: (2024)
por: Jin, Peng, et al.
Publicado: (2024)
SDG-MoE: Signed Debate Graph Mixture-of-Experts
por: Kulibaba, Stepan, et al.
Publicado: (2026)
por: Kulibaba, Stepan, et al.
Publicado: (2026)
Input Domain Aware MoE: Decoupling Routing Decisions from Task Optimization in Mixture of Experts
por: Hua, Yongxiang, et al.
Publicado: (2025)
por: Hua, Yongxiang, et al.
Publicado: (2025)
Symphony-MoE: Harmonizing Disparate Pre-trained Models into a Coherent Mixture-of-Experts
por: Wang, Qi, et al.
Publicado: (2025)
por: Wang, Qi, et al.
Publicado: (2025)
PWC-MoE: Privacy-Aware Wireless Collaborative Mixture of Experts
por: Su, Yang, et al.
Publicado: (2025)
por: Su, Yang, et al.
Publicado: (2025)
Flex-MoE: Modeling Arbitrary Modality Combination via the Flexible Mixture-of-Experts
por: Yun, Sukwon, et al.
Publicado: (2024)
por: Yun, Sukwon, et al.
Publicado: (2024)
EAC-MoE: Expert-Selection Aware Compressor for Mixture-of-Experts Large Language Models
por: Chen, Yuanteng, et al.
Publicado: (2025)
por: Chen, Yuanteng, et al.
Publicado: (2025)
MP-MoE: Matrix Profile-Guided Mixture of Experts for Precipitation Forecasting
por: Tran, Huyen Ngoc, et al.
Publicado: (2026)
por: Tran, Huyen Ngoc, et al.
Publicado: (2026)
FaST: Efficient and Effective Long-Horizon Forecasting for Large-Scale Spatial-Temporal Graphs via Mixture-of-Experts
por: Zhao, Yiji, et al.
Publicado: (2026)
por: Zhao, Yiji, et al.
Publicado: (2026)
MELON: Multimodal Mixture-of-Experts with Spectral-Temporal Fusion for Long-Term Mobility Estimation in Critical Care
por: Zhang, Jiaqing, et al.
Publicado: (2025)
por: Zhang, Jiaqing, et al.
Publicado: (2025)
Elastic MoE: Unlocking the Inference-Time Scalability of Mixture-of-Experts
por: Gu, Naibin, et al.
Publicado: (2025)
por: Gu, Naibin, et al.
Publicado: (2025)
I2MoE: Interpretable Multimodal Interaction-aware Mixture-of-Experts
por: Xin, Jiayi, et al.
Publicado: (2025)
por: Xin, Jiayi, et al.
Publicado: (2025)
MoE-DisCo:Low Economy Cost Training Mixture-of-Experts Models
por: Ye, Xin, et al.
Publicado: (2026)
por: Ye, Xin, et al.
Publicado: (2026)
Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts
por: Shi, Xiaoming, et al.
Publicado: (2024)
por: Shi, Xiaoming, et al.
Publicado: (2024)
Alloc-MoE: Budget-Aware Expert Activation Allocation for Efficient Mixture-of-Experts Inference
por: Liu, Baihui, et al.
Publicado: (2026)
por: Liu, Baihui, et al.
Publicado: (2026)
Joint MoE Scaling Laws: Mixture of Experts Can Be Memory Efficient
por: Ludziejewski, Jan, et al.
Publicado: (2025)
por: Ludziejewski, Jan, et al.
Publicado: (2025)
MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts
por: Pióro, Maciej, et al.
Publicado: (2024)
por: Pióro, Maciej, et al.
Publicado: (2024)
$μ$-MoE: Test-Time Pruning as Micro-Grained Mixture-of-Experts
por: Koike-Akino, Toshiaki, et al.
Publicado: (2025)
por: Koike-Akino, Toshiaki, et al.
Publicado: (2025)
DA-MoE: Addressing Depth-Sensitivity in Graph-Level Analysis through Mixture of Experts
por: Yao, Zelin, et al.
Publicado: (2024)
por: Yao, Zelin, et al.
Publicado: (2024)
MobileMoE: Scaling On-Device Mixture of Experts
por: Chen, Yanbei, et al.
Publicado: (2026)
por: Chen, Yanbei, et al.
Publicado: (2026)
HiMoE: Heterogeneity-Informed Mixture-of-Experts for Fair Spatial-Temporal Forecasting
por: Yu, Shaohan, et al.
Publicado: (2024)
por: Yu, Shaohan, et al.
Publicado: (2024)
MoE-I$^2$: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition
por: Yang, Cheng, et al.
Publicado: (2024)
por: Yang, Cheng, et al.
Publicado: (2024)
RQ-MoE: Residual Quantization via Mixture of Experts for Efficient Input-Dependent Vector Compression
por: Zhong, Zhengjia, et al.
Publicado: (2026)
por: Zhong, Zhengjia, et al.
Publicado: (2026)
TT-LoRA MoE: Unifying Parameter-Efficient Fine-Tuning and Sparse Mixture-of-Experts
por: Kunwar, Pradip, et al.
Publicado: (2025)
por: Kunwar, Pradip, et al.
Publicado: (2025)
L-MoE: End-to-End Training of a Lightweight Mixture of Low-Rank Adaptation Experts
por: Ji, Shihao, et al.
Publicado: (2025)
por: Ji, Shihao, et al.
Publicado: (2025)
Seg-MoE: Multi-Resolution Segment-wise Mixture-of-Experts for Time Series Forecasting Transformers
por: Ortigossa, Evandro S., et al.
Publicado: (2026)
por: Ortigossa, Evandro S., et al.
Publicado: (2026)
Exploiting the Experts: Unauthorized Compression in MoE-LLMs
por: Neogi, Pinaki Prasad Guha, et al.
Publicado: (2025)
por: Neogi, Pinaki Prasad Guha, et al.
Publicado: (2025)
Spatial-Temporal Mixture-of-Graph-Experts for Multi-Type Crime Prediction
por: Wu, Ziyang, et al.
Publicado: (2024)
por: Wu, Ziyang, et al.
Publicado: (2024)
Linear-MoE: Linear Sequence Modeling Meets Mixture-of-Experts
por: Sun, Weigao, et al.
Publicado: (2025)
por: Sun, Weigao, et al.
Publicado: (2025)
CP-MoE: Consistency-Preserving Mixture-of-Experts for Continual Learning
por: Liu, Yang, et al.
Publicado: (2026)
por: Liu, Yang, et al.
Publicado: (2026)
BrainNet-MoE: Brain-Inspired Mixture-of-Experts Learning for Neurological Disease Identification
por: Zhang, Jing, et al.
Publicado: (2025)
por: Zhang, Jing, et al.
Publicado: (2025)
MoE-Loco: Mixture of Experts for Multitask Locomotion
por: Huang, Runhan, et al.
Publicado: (2025)
por: Huang, Runhan, et al.
Publicado: (2025)
SD-MoE: Spectral Decomposition for Effective Expert Specialization
por: Huang, Ruijun, et al.
Publicado: (2026)
por: Huang, Ruijun, et al.
Publicado: (2026)
Expert Divergence Learning for MoE-based Language Models
por: Li, Jiaang, et al.
Publicado: (2026)
por: Li, Jiaang, et al.
Publicado: (2026)
AT-MoE: Adaptive Task-planning Mixture of Experts via LoRA Approach
por: Li, Xurui, et al.
Publicado: (2024)
por: Li, Xurui, et al.
Publicado: (2024)
Efficient Temporal Tokenization for Mobility Prediction with Large Language Models
por: He, Haoyu, et al.
Publicado: (2025)
por: He, Haoyu, et al.
Publicado: (2025)
MoST: Mixing Speech and Text with Modality-Aware Mixture of Experts
por: Lou, Yuxuan, et al.
Publicado: (2026)
por: Lou, Yuxuan, et al.
Publicado: (2026)
Ejemplares similares
-
RHYTHM: Reasoning with Hierarchical Temporal Tokenization for Human Mobility
por: He, Haoyu, et al.
Publicado: (2025) -
Mixture of Experts (MoE): A Big Data Perspective
por: Gan, Wensheng, et al.
Publicado: (2025) -
MoE-Health: A Mixture of Experts Framework for Robust Multimodal Healthcare Prediction
por: Wang, Xiaoyang, et al.
Publicado: (2025) -
MoE++: Accelerating Mixture-of-Experts Methods with Zero-Computation Experts
por: Jin, Peng, et al.
Publicado: (2024) -
SDG-MoE: Signed Debate Graph Mixture-of-Experts
por: Kulibaba, Stepan, et al.
Publicado: (2026)