推断两个事件序列之间的因果关系：基于语言模型的方法
Inferring Causal Relations between Two Sequences of Events with Language Models
- INRIA（法国国家信息与自动化研究所）
- Univ. Grenoble Alpes（格勒诺布尔大学）
- CNRS（法国国家科学研究中心）
- LIG（格勒诺布尔信息学实验室）
- Grenoble INP（格勒诺布尔理工学院）
- Nokia Bell Labs（诺基亚贝尔实验室）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本研究利用大型语言模型从仅两个事件序列中推断因果关系，在合成和真实数据上优于标准因果发现算法，为因果AI在有限信息场景下提供新方法。
AI中文摘要：
因果人工智能是人工智能的一个分支，它帮助理解和推理因果关系，而不仅仅是模式或相关性。因果发现旨在从观测数据以及（如果可用）干预数据中推断潜在因果结构的要素——通常表示为有向图。虽然因果发现是从单纯关联迈向真正理解的基本步骤，因此也是因果人工智能的基础构建块，但当必须从单一观测中推断因果关系时，它变得本质上困难。在这种情况下，标准的因果发现方法无法使用，人们必须从有限的信息中识别因果关系。这通常是例如由不同警报产生的事件序列的情况，这些序列需要实时分析以检测异常现象，而这些现象通常很少见。我们在这项研究中表明，可以利用大型语言模型（LLMs）的预测能力来推断仅两个事件序列之间的因果关系。这种方法在合成数据和真实数据上均得到验证，在多个时间序列数据上提供了比标准因果发现算法更好的结果，即使这些数据被转换为较小的、单一观测序列。
英文摘要：
Causal AI is a branch of Artificial Intelligence which helps understand and reason about cause and effect relationships, not just patterns or correlations. Causal discovery aims to infer elements of the underlying causal structure--often represented as a directed graph--from observational and, when available, interventional data. While causal discovery is the fundamental step for moving beyond mere associations toward genuine understanding, and thus the basic building block of causal AI, it becomes intrinsically difficult when causal relations must be inferred from single observations. In such situations, standard causal discovery methods cannot be used and one has to identify causal relations from limited amount of information. This is typically the case for, e.g., sequences of events produced by different alarms which need to be analyzed on the fly to detect abnormal phenomena, which are usually rare. We show in this study that it is possible to leverage the predictive power of Large Language Models (LLMs) to infer causal relations between only two sequences of events. This approach, which is validated on both synthetic and real data, provides better results than standard causal discovery algorithms on several time series data, even though these data were converted into smaller, single observed sequences.
