Formalizing and falsifying causal pathways of rare events

Computer Science > Artificial Intelligence [Submitted on 29 May 2026] Formalizing and falsifying causal pathways of rare events Anahita Haghighat, Dominik Janzing Building on recent formalizations of root cause analysis for rare events (``outliers'') in structural equation models, we propose a formal definition of a causal pathway and discuss its testable implications. We identify conditions under which these implications depend only on a causal abstraction defined by the pathway of rare events, rather than on the full causal graph of the underlying system. Accordingly, we introduce an abstraction of causal structure to pathways of rare events that bridges simple verbal causal explanations and detailed causal modeling. Comments: accepted for ICML 2026 Subjects: Artificial Intelligence (cs.AI) MSC classes: 62A01 ACM classes: G.3 Cite as: arXiv:2605.31254 [cs.AI]   (or arXiv:2605.31254v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2605.31254 Focus to learn more Submission history From: Dominik Janzing [view email] [v1] Fri, 29 May 2026 12:50:47 UTC (138 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-05 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)