7 papers
Speaking Numbers to LLMs: Multi-Wavelet Number Embeddings for Time Series Forecasting
Defu Cao, Zijie Lei, Muyan Weng +2
Large language models (LLMs) are attractive for context-aware time series forecasting because they can integrate heterogeneous textual signals, yet their discrete, language-oriente…
A Survey of Reasoning and Agentic Systems in Time Series with Large Language Models
Ching Chang, Yidan Shi, Defu Cao +8
Time series reasoning treats time as a first-class axis and incorporates intermediate evidence directly into the answer. This survey defines the problem and organizes the literatur…
TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis
Wen Ye, Wei Yang, Defu Cao +4
Time series analysis is crucial in real-world applications, yet traditional methods focus on isolated tasks only, and recent studies on time series reasoning remain limited to eith…
Adaptive Collaboration with Humans: Metacognitive Policy Optimization for Multi-Agent LLMs with Continual Learning
Wei Yang, Defu Cao, Jiacheng Pang +2
While scaling individual Large Language Models (LLMs) has delivered remarkable progress, the next frontier lies in scaling collaboration through multi-agent systems (MAS). However,…
When LLM Meets Time Series: Can LLMs Perform Multi-Step Time Series Reasoning and Inference
Wen Ye, Jinbo Liu, Defu Cao +2
The rapid advancement of Large Language Models (LLMs) has sparked growing interest in their application to time series analysis tasks. However, their ability to perform complex rea…
Foundation Models for Demand Forecasting via Dual-Strategy Ensembling
Wei Yang, Defu Cao, Yan Liu
Accurate demand forecasting is critical for supply chain optimization, yet remains difficult in practice due to hierarchical complexity, domain shifts, and evolving external factor…