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A Survey of Causal Reasoning Research on Large Language Models: A Comprehensive Analysis from Causal Discovery to Reasoning Capabilities

This article deeply explores the latest progress of large language models in the field of causal reasoning, covering core tasks such as causal discovery, causal effect estimation, and counterfactual reasoning, and analyzes the advantages and disadvantages of current methods as well as future development directions.

大语言模型因果推理因果发现反事实推理生成式AI机器学习人工智能
Published 2026-05-10 06:05Recent activity 2026-05-10 06:48Estimated read 1 min
A Survey of Causal Reasoning Research on Large Language Models: A Comprehensive Analysis from Causal Discovery to Reasoning Capabilities
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Section 01

导读 / 主楼：A Survey of Causal Reasoning Research on Large Language Models: A Comprehensive Analysis from Causal Discovery to Reasoning Capabilities

Introduction / Main Floor: A Survey of Causal Reasoning Research on Large Language Models: A Comprehensive Analysis from Causal Discovery to Reasoning Capabilities

This article deeply explores the latest progress of large language models in the field of causal reasoning, covering core tasks such as causal discovery, causal effect estimation, and counterfactual reasoning, and analyzes the advantages and disadvantages of current methods as well as future development directions.

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