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Can LLM Coding Agents Reason About Time Series?
探究大模型编码代理在时间序列推理上的边界，揭示当前AI的局限与潜力。
arXiv:2606.16545v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly being used for automated decision-making systems in fina…
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Harnessing Generalist Agents for Contextualized Time Series
通用智能体如何理解并处理带上下文的时间序列？最新arXiv论文给出系统性探索。
arXiv:2606.05404v1 Announce Type: new Abstract: Time series are often embedded in rich contexts that are essential for holistic modeling. Moreover, re…
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Continuity and Ordinality Matter: Constraining Time Series Tokens for Effective Time Series Analysis with Large Language Models
全新方法约束时序token的连续性与序数性，大幅提升LLM处理时间序列任务的性能与理解力。
arXiv:2605.28866v1 Announce Type: cross Abstract: Token-based time series large language models (TS-LLMs) have emerged as a promising direction for ti…
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QuChaTeR: A Hybrid Quantum-Chaotic Temporal Framework for Earthquake Prediction
QuChaTeR 结合量子计算与混沌映射，构建新型混合框架提升地震预测精度，兼具理论创新与实用潜力
arXiv:2605.16454v1 Announce Type: new Abstract: Seismic prediction remains challenging due to the highly nonlinear and chaotic dynamics of earthquake …