# Evaluating Causal Reasoning in LLMs: A Case Study in the Challenges of Procedural Generation

> 全文为英语

**Published:** 2026年10月30日
**Author:** Justin Clarke, Isha Karn, Patrick Murray, KJ Hill, David Jensen
**Source:** arXiv — cs.AI
**Language:** en-US
**HTML:** https://aiqazaqstan.com/zh/articles/evaluating-causal-reasoning-in-llms-a-case-study-in-the-challenges-of-pr

arXiv:2610.38100v1 Announce Type: new Abstract: Large language models (LLMs) appear to represent and reason about a large range of phenomena. In particular, recent studies have examined whether LLMs can accurately reason about causation. One of the most commonly used benchmarks…

> 内容来自原始来源： **arXiv — cs.AI**
> [在 arXiv — cs.AI 阅读全文](https://arxiv.org/abs/2610.38100)

**标签：** #Papers with Code #arXiv

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