12 papers
TiCT: A Synthetically Pre-Trained Foundation Model for Time Series Classification
Chin-Chia Michael Yeh, Uday Singh Saini, Junpeng Wang +5
The ubiquity of time series data creates a strong demand for general-purpose foundation models, yet developing them for classification remains a significant challenge, largely due…
TREASURE: The Visa Payment Foundation Model for High-Volume Transaction Understanding
Chin-Chia Michael Yeh, Uday Singh Saini, Xin Dai +12
Payment networks form the backbone of modern commerce, generating high volumes of transaction records from daily activities. Properly modeling this data can enable applications suc…
TransactionGPT
Yingtong Dou, Zhimeng Jiang, Tianyi Zhang +26
We present TransactionGPT (TGPT), a foundation model for consumer transaction data within one of the world's largest payment networks. TGPT is designed to understand and generate t…
Empowering Time Series Forecasting with LLM-Agents
Chin-Chia Michael Yeh, Vivian Lai, Uday Singh Saini +5
Large Language Model (LLM) powered agents have emerged as effective planners for Automated Machine Learning (AutoML) systems. While most existing AutoML approaches focus on automat…
Towards Efficient Large Scale Spatial-Temporal Time Series Forecasting via Improved Inverted Transformers
Jiarui Sun, Chin-Chia Michael Yeh, Yujie Fan +10
Time series forecasting at scale presents significant challenges for modern prediction systems, particularly when dealing with large sets of synchronized series, such as in a globa…
Visual Attention Exploration in Vision-Based Mamba Models
Junpeng Wang, Chin-Chia Michael Yeh, Uday Singh Saini +1
State space models (SSMs) have emerged as an efficient alternative to transformer-based models, offering linear complexity that scales better than transformers. One of the latest a…