5 papers
LLMSynthor: Macro-Aligned Micro-Records Synthesis with Large Language Models
Yihong Tang, Menglin Kong, Junlin He +3
Macro-aligned micro-records are crucial for credible simulations in social science and urban studies. For example, epidemic models are only reliable when individual-level mobility…
Dr-CiK: A Testbed for Foresight-Driven Agents
Yihong Tang, Andrew Robert Williams, Arjun Ashok +6
Time series forecasting in real-world settings often depends not only on historical observations, but also on external context that must be actively discovered from noisy, heteroge…
Frequency-Constrained Learning for Long-Term Forecasting
Menglin Kong, Vincent Zhihao Zheng, Lijun Sun
Many real-world time series exhibit strong periodic structures arising from physical laws, human routines, or seasonal cycles. However, modern deep forecasting models often fail to…
Dynamic Modes as Time Representation for Spatiotemporal Forecasting
Menglin Kong, Vincent Zhihao Zheng, Xudong Wang +1
This paper introduces a data-driven time embedding method for modeling long-range seasonal dependencies in spatiotemporal forecasting tasks. The proposed approach employs Dynamic M…
MVG-CRPS: A Robust Loss Function for Multivariate Probabilistic Forecasting
Vincent Zhihao Zheng, Lijun Sun
Multivariate Gaussian (MVG) distributions are central to modeling correlated continuous variables in probabilistic forecasting. Neural forecasting models typically parameterize the…