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Yaguo Liu

2 accepted papers

2026

CoGenCast: A Coupled Autoregressive–Flow Generative Framework for Time Series Forecasting

ICML 2026poster

Time series forecasting can be viewed as a generative problem that requires both semantic understanding over contextual conditions and stochastic modeling of continuous temporal dynamics. Existing approaches typically rely on either autoregressive large language models (LLMs) for semantic context mo…

Cited by 0SourceScholar
2026

MemCast: Memory-Driven Time Series Forecasting with Experience-Conditioned Reasoning

ICML 2026poster

Time series forecasting (TSF) plays a critical role in decision-making for many real-world applications. Recently, LLM-based forecasters have made promising advancements. Despite their effectiveness, existing methods often lack explicit experience accumulation and continual evolution. In this work, …

Cited by 0SourceScholar