Takashi Kameyama, Masahiro Kato, Yasuko Hio, Yasushi Takano, Naoto Minakawa
arXiv 4 Mar 2026 · Machine Learning
arXiv:2603.04276 · PDF · DOI · OpenAlex · Extracted main text
Large language models (LLMs) are trained on enormous amounts of data and encode knowledge in their parameters. We propose a pipeline to elicit causal relationships from LLMs. Specifically, (i) we sample many documents from LLMs on a given topic, (ii) we extract an event list from from each document, (iii) we group events that appear across documents into canonical events, (iv) we construct a binary indicator vector for each document over canonical events, and (v) we estimate candidate causal graphs using causal discovery methods. Our approach does not guarantee real-world causality. Rather, it provides a framework for presenting the set of causal hypotheses that LLMs can plausibly assume, as an inspectable set of variables and candidate graphs.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Judea Pearl (2000) Causality: Models, Reasoning, and Inference | 0.511 | 2 | 1 | 100% |
| 2 | David Maxwell Chickering (2002) Optimal structure identification with greedy search | 0.405 | 1 | 1 | 100% |
| 3 | P. Christen (2012) Data Matching: Concepts and Techniques for Record Linkage, Entity Resolution, and Duplicate Detection | 0.405 | 1 | 1 | 100% |
| 4 | Agata Cybulska and Piek Vossen (2014) Using a sledgehammer to crack a nut? lexical diversity and event coreference resolution | 0.405 | 1 | 1 | 100% |
| 5 | Ahmed K. Elmagarmid, Panagiotis G. Ipeirotis, and Vassilios S. Veryk… (2007) Duplicate record detection: A survey | 0.405 | 1 | 1 | 100% |
| 6 | Ivan P. Fellegi and Alan B. Sunter (1969) A theory for record linkage | 0.405 | 1 | 1 | 100% |
| 7 | Matthew Gentzkow, Bryan Kelly, and Matt Taddy (2019) Text as data | 0.405 | 1 | 1 | 100% |
| 8 | Justin Grimmer and Brandon M. Stewart (2013) Text as data: The promise and pitfalls of automatic content analysis methods for political texts | 0.405 | 1 | 1 | 100% |
| 9 | Oktie Hassanzadeh, Debarun Bhattacharjya, Mark Feblowitz, Kavitha Sr… (2020) Causal knowledge extraction through large-scale text mining | 0.405 | 1 | 1 | 100% |
| 10 | Guido W. Imbens and Donald B. Rubin (2015) Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 19 scored citations.