:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Lin, Chenguo, Wen, Xumeng, Cao, Wei, Huang, Congrui, Bian, Jiang, Lin, Stephen, Wu, Zhirong
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2310.07402
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Large Language Model as a Universal Clinical Multi-task Decoder
by: Wu, Yujiang, et al.
Published: (2024)

TimeDP: Learning to Generate Multi-Domain Time Series with Domain Prompts
by: Huang, Yu-Hao, et al.
Published: (2025)

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models
by: Wen, Xumeng, et al.
Published: (2025)

Scalable Numerical Embeddings for Multivariate Time Series: Enhancing Healthcare Data Representation Learning
by: Huang, Chun-Kai, et al.
Published: (2024)

Output Scaling: YingLong-Delayed Chain of Thought in a Large Pretrained Time Series Forecasting Model
by: Wang, Xue, et al.
Published: (2025)

MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process
by: Fan, Xinyao, et al.
Published: (2024)

MillGNN: Learning Multi-Scale Lead-Lag Dependencies for Multi-Variate Time Series Forecasting
by: Wu, Binqing, et al.
Published: (2025)

When LLM Meets Time Series: Can LLMs Perform Multi-Step Time Series Reasoning and Inference
by: Ye, Wen, et al.
Published: (2025)

Large-Scale Network Embedding in Apache Spark
by: Lin, Wenqing
Published: (2021)

Higher-order Cross-structural Embedding Model for Time Series Analysis
by: Lin, Guancen, et al.
Published: (2024)

ElasTST: Towards Robust Varied-Horizon Forecasting with Elastic Time-Series Transformer
by: Zhang, Jiawen, et al.
Published: (2024)

Empowering Time Series Analysis with Large-Scale Multimodal Pretraining
by: Chen, Peng, et al.
Published: (2026)

SDGF: Fusing Static and Multi-Scale Dynamic Correlations for Multivariate Time Series Forecasting
by: Wang, Shaoxun, et al.
Published: (2025)

Are Time-Series Foundation Models Deployment-Ready? A Systematic Study of Adversarial Robustness Across Domains
by: Zhang, Jiawen, et al.
Published: (2025)

Scaling LLM Test-Time Compute with Mobile NPU on Smartphones
by: Hao, Zixu, et al.
Published: (2025)

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

TimeSeriesExamAgent: Creating Time Series Reasoning Benchmarks at Scale
by: Gwiazda, Malgorzata, et al.
Published: (2026)

Scaling Law for Time Series Forecasting
by: Shi, Jingzhe, et al.
Published: (2024)

MedFuse: Multiplicative Embedding Fusion For Irregular Clinical Time Series
by: Hsieh, Yi-Hsien, et al.
Published: (2025)

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

Rethinking Reward Models for Multi-Domain Test-Time Scaling
by: Lee, Dong Bok, et al.
Published: (2025)

DisMS-TS: Eliminating Redundant Multi-Scale Features for Time Series Classification
by: Liu, Zhipeng, et al.
Published: (2025)

Spatial Transcriptomics as Images for Large-Scale Pretraining
by: Zhu, Yishun, et al.
Published: (2026)

Exploring Scalability in Large-Scale Time Series in DeepVATS framework
by: Santamaria-Valenzuela, Inmaculada, et al.
Published: (2024)

Towards Neural Scaling Laws for Time Series Foundation Models
by: Yao, Qingren, et al.
Published: (2024)

A Multi-Scale Decomposition MLP-Mixer for Time Series Analysis
by: Zhong, Shuhan, et al.
Published: (2023)

DMSC: Dynamic Multi-Scale Coordination Framework for Time Series Forecasting
by: Yang, Haonan, et al.
Published: (2025)

Toward Physics-guided Time Series Embedding
by: Hu, Jiaxi, et al.
Published: (2024)

Towards Thinking-Optimal Scaling of Test-Time Compute for LLM Reasoning
by: Yang, Wenkai, et al.
Published: (2025)

Time-RA: Towards Time Series Reasoning for Anomaly Diagnosis with LLM Feedback
by: Yang, Yiyuan, et al.
Published: (2025)

CoDiQ: Test-Time Scaling for Controllable Difficult Question Generation
by: Peng, Zhongyuan, et al.
Published: (2026)

Multi-Scale Dilated Convolution Network for Long-Term Time Series Forecasting
by: Li, Feifei, et al.
Published: (2024)

DRFormer: Multi-Scale Transformer Utilizing Diverse Receptive Fields for Long Time-Series Forecasting
by: Ding, Ruixin, et al.
Published: (2024)

Timely Machine: Awareness of Time Makes Test-Time Scaling Agentic
by: Ma, Yichuan, et al.
Published: (2026)

Timer-S1: A Billion-Scale Time Series Foundation Model with Serial Scaling
by: Liu, Yong, et al.
Published: (2026)

A Stock Price Prediction Approach Based on Time Series Decomposition and Multi-Scale CNN using OHLCT Images
by: Pei, Zhiyuan, et al.
Published: (2024)

Does Scaling Law Apply in Time Series Forecasting?
by: Li, Zeyan, et al.
Published: (2025)

Diversified Scaling Inference in Time Series Foundation Models
by: Hua, Ruijin, et al.
Published: (2026)

Beyond Model Scaling: Test-Time Intervention for Efficient Deep Reasoning
by: Wang, Qianyue, et al.
Published: (2026)

MegaScale-Data: Scaling Dataloader for Multisource Large Foundation Model Training
by: Zhao, Juntao, et al.
Published: (2025)