Cover Image

Multi-Modal Time Series Prediction via Mixture of Modulated Experts

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Lige, Maatouk, Ali, Chen, Jialin, Tassiulas, Leandros, Ying, Rex
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Tele-LLMs: A Series of Specialized Large Language Models for Telecommunications
by: Maatouk, Ali, et al.
Published: (2024)

HELM: Hyperbolic Large Language Models via Mixture-of-Curvature Experts
by: He, Neil, et al.
Published: (2025)

LitBench: A Graph-Centric Large Language Model Benchmarking Tool For Literature Tasks
by: Varvarigos, Andreas, et al.
Published: (2026)

From Similarity to Superiority: Channel Clustering for Time Series Forecasting
by: Chen, Jialin, et al.
Published: (2024)

TRACE: Grounding Time Series in Context for Multimodal Embedding and Retrieval
by: Chen, Jialin, et al.
Published: (2025)

Parameter-Efficient Fine-Tuning of LLMs with Mixture of Space Experts
by: Zhang, Buze, et al.
Published: (2026)

MTBench: A Multimodal Time Series Benchmark for Temporal Reasoning and Question Answering
by: Chen, Jialin, et al.
Published: (2025)

Over-the-Air Federated Learning via Weighted Aggregation
by: Azimi-Abarghouyi, Seyed Mohammad, et al.
Published: (2024)

Predictive Handover Strategy in 6G and Beyond: A Deep and Transfer Learning Approach
by: Panitsas, Ioannis, et al.
Published: (2024)

SANDWICH: Towards an Offline, Differentiable, Fully-Trainable Wireless Neural Ray-Tracing Surrogate
by: Jin, Yifei, et al.
Published: (2024)

Efficient High-Resolution Time Series Classification via Attention Kronecker Decomposition
by: Feng, Aosong, et al.
Published: (2024)

Wavelet Mixture of Experts for Time Series Forecasting
by: Zhou, Zheng, et al.
Published: (2025)

MoFE-Time: Mixture of Frequency Domain Experts for Time-Series Forecasting Models
by: Liu, Yiwen, et al.
Published: (2025)

AME-TS: Anchored Mixture-of-Experts for Time Series Forecasting
by: Wang, Rui, et al.
Published: (2026)

Mixture-of-Linear-Experts for Long-term Time Series Forecasting
by: Ni, Ronghao, et al.
Published: (2023)

Reasoning through Verifiable Forecast Actions: Consistency-Grounded RL for Financial LLMs
by: Chen, Jialin, et al.
Published: (2026)

A Family of Open Time-Series Foundation Models for the Radio Access Network
by: Panitsas, Ioannis, et al.
Published: (2026)

Flex-MoE: Modeling Arbitrary Modality Combination via the Flexible Mixture-of-Experts
by: Yun, Sukwon, et al.
Published: (2024)

Fin-RATE: A Real-world Financial Analytics and Tracking Evaluation Benchmark for LLMs on SEC Filings
by: Jiang, Yidong, et al.
Published: (2026)

Graph Mixture of Experts and Memory-augmented Routers for Multivariate Time Series Anomaly Detection
by: Huang, Xiaoyu, et al.
Published: (2024)

Seg-MoE: Multi-Resolution Segment-wise Mixture-of-Experts for Time Series Forecasting Transformers
by: Ortigossa, Evandro S., et al.
Published: (2026)

Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts
by: Shi, Xiaoming, et al.
Published: (2024)

MoHETS: Long-term Time Series Forecasting with Mixture-of-Heterogeneous-Experts
by: Ortigossa, Evandro S., et al.
Published: (2026)

Klotski: Efficient Mixture-of-Expert Inference via Expert-Aware Multi-Batch Pipeline
by: Fang, Zhiyuan, et al.
Published: (2025)

M$^2$FMoE: Multi-Resolution Multi-View Frequency Mixture-of-Experts for Extreme-Adaptive Time Series Forecasting
by: Huang, Yaohui, et al.
Published: (2026)

Position: Beyond Euclidean -- Foundation Models Should Embrace Non-Euclidean Geometries
by: He, Neil, et al.
Published: (2025)

STM3: Mixture of Multiscale Mamba for Long-Term Spatio-Temporal Time-Series Prediction
by: Chen, Haolong, et al.
Published: (2025)

Spatial-Temporal Mixture-of-Graph-Experts for Multi-Type Crime Prediction
by: Wu, Ziyang, et al.
Published: (2024)

WaveMoE: A Wavelet-Enhanced Mixture-of-Experts Foundation Model for Time Series Forecasting
by: Wu, Shunyu, et al.
Published: (2026)

MoDEx: Mixture of Depth-specific Experts for Multivariate Long-term Time Series Forecasting
by: Yoon, Hyekyung, et al.
Published: (2026)

Dynamic Adaptive Shared Experts with Grouped Multi-Head Attention Mixture of Experts
by: Li, Cheng, et al.
Published: (2025)

HypRAG: Hyperbolic Dense Retrieval for Retrieval Augmented Generation
by: Madhu, Hiren, et al.
Published: (2026)

HyperCore: The Core Framework for Building Hyperbolic Foundation Models with Comprehensive Modules
by: He, Neil, et al.
Published: (2025)

LeMoLE: LLM-Enhanced Mixture of Linear Experts for Time Series Forecasting
by: Zhang, Lingzheng, et al.
Published: (2024)

sDREAMER: Self-distilled Mixture-of-Modality-Experts Transformer for Automatic Sleep Staging
by: Chen, Jingyuan, et al.
Published: (2025)

SST: Multi-Scale Hybrid Mamba-Transformer Experts for Time Series Forecasting
by: Xu, Xiongxiao, et al.
Published: (2024)

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting
by: Pan, Licheng, et al.
Published: (2025)

MC#: Mixture Compressor for Mixture-of-Experts Large Models
by: Huang, Wei, et al.
Published: (2025)

Parameter-Efficient Routed Fine-Tuning: Mixture-of-Experts Demands Mixture of Adaptation Modules
by: Liu, Yilun, et al.
Published: (2025)

Efficiently Editing Mixture-of-Experts Models with Compressed Experts
by: He, Yifei, et al.
Published: (2025)