Ching Chang

According to our database, Ching Chang authored at least 11 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

MemPromptTSS: Persistent Prompt Memory for Iterative Multi-Granularity Time Series State Segmentation.

Ching Chang, Ming-Chih Lo, Chiao-Tung Chan, Wen-Chih Peng, Tien-Fu Chen

CoRR, October, 2025

A Survey of Reasoning and Agentic Systems in Time Series with Large Language Models.

Ching Chang, Yidan Shi, Defu Cao, Wei Yang, Jeehyun Hwang, Haixin Wang, Jiacheng Pang, Wei Wang, Yan Liu, Wen-Chih Peng, Tien-Fu Chen

CoRR, September, 2025

LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters.

Ching Chang, Wei-Yao Wang, Wen-Chih Peng, Tien-Fu Chen

ACM Trans. Intell. Syst. Technol., June, 2025

Time-IMM: A Dataset and Benchmark for Irregular Multimodal Multivariate Time Series.

Ching Chang, Jeehyun Hwang, Yidan Shi, Haixin Wang, Wen-Chih Peng, Tien-Fu Chen, Wei Wang

CoRR, June, 2025

FD-Bench: A Modular and Fair Benchmark for Data-driven Fluid Simulation.

Haixin Wang, Ruoyan Li, Fred Xu, Fang Sun, Kaiqiao Han, Zijie Huang, Guancheng Wan, Ching Chang, Xiao Luo, Wei Wang, Yizhou Sun

CoRR, May, 2025

PromptTSS: A Prompting-Based Approach for Interactive Multi-Granularity Time Series Segmentation.

Ching Chang, Ming-Chih Lo, Wen-Chih Peng, Tien-Fu Chen

Proceedings of the 34th ACM International Conference on Information and Knowledge Management, 2025

2024

TimeDRL: Disentangled Representation Learning for Multivariate Time-Series.

Ching Chang, Chiao-Tung Chan, Wei-Yao Wang, Wen-Chih Peng, Tien-Fu Chen

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

COKE: Causal Discovery with Chronological Order and Expert Knowledge in High Proportion of Missing Manufacturing Data.

Ting-Yun Ou, Ching Chang, Wen-Chih Peng

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Root Cause Analysis in Microservice Using Neural Granger Causal Discovery.

Cheng-Ming Lin, Ching Chang, Wei-Yao Wang, Kuang-Da Wang, Wen-Chih Peng

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

LLM4TS: Two-Stage Fine-Tuning for Time-Series Forecasting with Pre-Trained LLMs.

Ching Chang, Wen-Chih Peng, Tien-Fu Chen

CoRR, 2023

Detecting and Ranking Causal Anomalies in End-to-End Complex System.

Ching Chang, Cheng-Han Yeh, Wen-Chih Peng

CoRR, 2023