---
title: "Who cites Sycophancy in Large Language — 30 citing papers"
description: "30 papers of the Elamur Research library cite «Sycophancy in Large Language Models: Causes and Mitigations», found in their…"
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---
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# Who cites «Sycophancy in Large Language Models: Causes and Mitigations»

30 papers of our library cite it (of the 149,439 whose bibliographies we read) · 11 with a page here, the most cited first · [← back to «Sycophancy in Large Language Models: Causes and Mitigations»](https://md.research.elamur.ai/free/en/papers/malmqvist-2024-sycophancy-large-language-models-causes/)

1. **[ELEPHANT: Measuring and understanding social sycophancy in LLMs](https://md.research.elamur.ai/free/en/papers/cheng-2025-elephant-measuring-understanding-social-sycophancy/) [Science](https://md.research.elamur.ai/free/en/venues/science/)**Myra Cheng, Sunny Yu, Cinoo Lee, et al.*2025 · 188 citations*
2. [**Cancer-Myth: Evaluating Large Language Models on Patient Questions with False Presuppositions arXiv:2504.11373**Wang Bill Zhu, Tianqi Chen, Xinyan Velocity Yu, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-cancer-myth-evaluating-large-language/)
3. **[Flattery in Motion: Benchmarking and Analyzing Sycophancy in Video-LLMs](https://md.research.elamur.ai/free/en/papers/zhou-2026-flattery-motion-benchmarking-analyzing-sycophancy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenrui Zhou, Mohamed Hendy, Shu Yang, et al.*2026 · 6 citations*
4. **[Sycophants in the Courtroom: Are LLMs Fragile to Juridical Authority and Evolving Legal Standards?](https://md.research.elamur.ai/free/en/papers/molfetta-2026-sycophants-courtroom-are-llms-fragile/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lorenzo Molfetta, Alessio Cocchieri, Luca Ragazzi, et al.*2026 · 2 citations*
5. **[Sounding vs. Being an Expert: Disentangling Authority, Register and Cultural Impact in Sycophantic LLMs](https://md.research.elamur.ai/free/en/papers/maraia-2026-sounding-vs-being-expert-disentangling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Gabriele Maraia, Fabio Massimo Zanzotto, Leonardo Ranaldi*2026 · 1 citation*
6. **[SycoBench-600: Measuring Sycophancy and Correction Selectivity in LLM Assistants](https://md.research.elamur.ai/free/en/papers/sinha-2026-sycobench-600-measuring-sycophancy-correction/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Debu Sinha*2026 · 1 citation*
7. **[Choose Your Lens: Multi-Perspective Value Alignment of Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/zhao-2026-choose-your-lens-multi-perspective/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Gejian Zhao, Hanzhou Wu, Xinpeng Zhang*2026*
8. **[Feeling Right vs. Being Right: How AI Sycophancy Affects Value-Laden Deliberation](https://md.research.elamur.ai/free/en/papers/ryu-2026-feeling-right-vs-being-right/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jeongwoo Ryu, Soomin Kim, Jinsu Eun, et al.*2026*
9. **[Reasoning Hijacking: The Fragility of Reasoning Alignment in Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2026-reasoning-hijacking-fragility-reasoning-alignment/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuansen Liu, Yixuan Tang, Anthony Kum Hoe Tung*2026*
10. **[When Correct Beliefs Collapse: Epistemic Resilience of LLMs under Clinical Pressure](https://md.research.elamur.ai/free/en/papers/xiao-2026-when-correct-beliefs-collapse-epistemic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Boyu Xiao, Xiuqi Tian, Xuwen Song, et al.*2026*
11. **[Who Generates More Empathetic Responses–-Humans or LLMs? A Comparative Evaluation with Human and LLM Judges](https://md.research.elamur.ai/free/en/papers/welivita-2026-who-generates-more-empathetic-responses/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Anuradha Welivita, Fawzia Zeitoun, Pearl Pu*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/malmqvist-2024-sycophancy-large-language-models-causes/) — Sycophancy in Large Language Models: Causes and Mitigations
