---
title: "Who cites How to Catch an AI Liar: Lie — 23 citing papers"
description: "23 papers of the Elamur Research library cite «How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions»…"
canonical: "https://research.elamur.ai/free/en/papers/pacchiardi-2023-catch-ai-liar-lie-detection/cited-by/"
---
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# Who cites «How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions»

23 papers of our library cite it (of the 149,439 whose bibliographies we read) · 9 with a page here, the most cited first · [← back to «How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions»](https://md.research.elamur.ai/free/en/papers/pacchiardi-2023-catch-ai-liar-lie-detection/)

1. **[A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,231 citations*
2. **[Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting](https://md.research.elamur.ai/free/en/papers/turpin-2023-language-models-don-t-always/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Miles Turpin, Julian Michael, Ethan Perez, et al.*2023 · 586 citations*
3. [**XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models arXiv:2308.01263**Paul Rottger, Hannah Rose Kirk, Bertie Vidgen, et al.*2023 · 244 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2023-xstest-test-suite-identifying-exaggerated/)
4. [**AI Alignment: A Comprehensive Survey arXiv:2310.19852**Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.*2023 · 173 citations*](https://md.research.elamur.ai/free/en/papers/ji-2023-ai-alignment-comprehensive-survey/)
5. [**Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision arXiv:2312.09390**Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, et al.*2023 · 172 citations*](https://md.research.elamur.ai/free/en/papers/burns-2023-weak-strong-generalization-eliciting-strong/)
6. **[Alignment for Honesty](https://md.research.elamur.ai/free/en/papers/yang-2023-alignment-honesty/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuqing Yang, Ethan Chern, Xipeng Qiu, et al.*2023 · 90 citations*
7. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/)
8. [**Monitoring Reasoning Models for Misbehavior and the Risks of Promoting Obfuscation arXiv:2503.11926**Bowen Baker, Joost Huizinga, Leo Gao, et al.*2025 · 63 citations*](https://md.research.elamur.ai/free/en/papers/baker-2025-monitoring-reasoning-models-misbehavior-risks/)
9. **[Curing Miracle Steps in LLM Mathematical Reasoning with Rubric Rewards](https://md.research.elamur.ai/free/en/papers/yuan-2026-curing-miracle-steps-llm-mathematical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Youliang Yuan, Qiuyang Mang, Jingbang Chen, et al.*2026*

14 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/pacchiardi-2023-catch-ai-liar-lie-detection/) — How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions