5 papers · 1 filter
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…
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,…
TemporalBench: A Benchmark for Evaluating LLM-Based Agents on Contextual and Event-Informed Time Series Tasks
Muyan Weng, Defu Cao, Wei Yang +2
It is unclear whether strong forecasting performance reflects genuine temporal understanding or the ability to reason under contextual and event-driven conditions. We introduce Tem…
Conversational Time Series Foundation Models: Towards Explainable and Effective Forecasting
Defu Cao, Michael Gee, Jinbo Liu +4
The proliferation of time series foundation models has created a landscape where no single method achieves consistent superiority, framing the central challenge not as finding the…
An Examination on the Effectiveness of Divide-and-Conquer Prompting in Large Language Models
Yizhou Zhang, Lun Du, Defu Cao +2
Foundation models, such as Large language Models (LLMs), have attracted significant amount of interest due to their large number of applications. However, when handling tasks invol…