9 papers
CastFSR: A Fast--Slow--Reflect Agentic Reasoning Framework for Context-Aware Time Series Forecasting
Xiaoyu Tao, Mingyue Cheng, Bokai Pan +6
Time series forecasting is fundamental to decision-making in complex systems, where future dynamics are influenced not only by historical observations but also by evolving contextu…
AnomaMind: Agentic Time Series Anomaly Detection with Tool-Augmented Reasoning
Xiaoyu Tao, Yuchong Wu, Mingyue Cheng +2
Time series anomaly detection is critical in many real-world applications, where effective solutions must localize anomalous regions and support reliable decision-making under comp…
AlphaCast: A Human Wisdom-LLM Intelligence Co-Reasoning Framework for Interactive Time Series Forecasting
Xiaohan Zhang, Tian Gao, Mingyue Cheng +5
Time series forecasting plays a crucial role in decision-making across many real-world applications. Despite substantial progress, most existing methods still treat forecasting as…
Cast-R1: Learning Tool-Augmented Sequential Decision Policies for Time Series Forecasting
Xiaoyu Tao, Mingyue Cheng, Chuang Jiang +3
Time series forecasting has long been dominated by model-centric approaches that formulate prediction as a single-pass mapping from historical observations to future values. Despit…
Towards Context-aware Reasoning-enhanced Generative Searching in E-commerce
Zhiding Liu, Ben Chen, Mingyue Cheng +6
Search-based recommendation is one of the most critical application scenarios in e-commerce platforms. Users' complex search contexts--such as spatiotemporal factors, historical in…
STaR: Towards Effective and Stable Table Reasoning via Slow-Thinking Large Language Models
Huajian Zhang, Mingyue Cheng, Yucong Luo +1
Table reasoning with large language models (LLMs) plays a critical role in building intelligent systems capable of understanding and analyzing tabular data. Despite recent progress…