---
title: "Sounding vs. Being an Expert — paper by Maraia et al. (2026)"
description: "They build the Sycophancy Matrix, a 2×2 adversarial benchmark that crosses high/low authority with high/low register. 25 references."
authors: ["Gabriele Maraia", "Fabio Massimo Zanzotto", "Leonardo Ranaldi"]
year: 2026
venue: "Findings of the Association for Computational Linguistics: ACL 2026"
source: "https://aclanthology.org/2026.findings-acl.1627/"
doi: "10.18653/v1/2026.findings-acl.1627"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/maraia-2026-sounding-vs-being-expert-disentangling/"
---
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# Sounding vs. Being an Expert: Disentangling Authority, Register and Cultural Impact in Sycophantic LLMs

**Authors:** [Gabriele Maraia](https://md.research.elamur.ai/free/en/authors/gabriele-maraia/), [Fabio Massimo Zanzotto](https://md.research.elamur.ai/free/en/authors/fabio-massimo-zanzotto/) and [Leonardo Ranaldi](https://md.research.elamur.ai/free/en/authors/leonardo-ranaldi/) · **Year:** 2026 · **Venue:** [Findings of the Association for Computational Linguistics: ACL 2026](https://md.research.elamur.ai/free/en/venues/findings/) ([Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2026.findings-acl.1627/) · [PDF](https://aclanthology.org/2026.findings-acl.1627.pdf) · [DOI 10.18653/v1/2026.findings-acl.1627](https://doi.org/10.18653/v1/2026.findings-acl.1627) · [OpenAlex](https://openalex.org/W7166882628)

**Citations:** 1 citations (OpenAlex, 2026-10-14)

## Summary
The paper examines why LLMs abandon correct answers when users push back. It treats sycophancy as a sociolinguistic effect rather than a purely technical flaw. The authors separate two sources of perceived credibility: stated credentials (explicit authority) and polished, formal style (implicit authority through register). They build the Sycophancy Matrix, a 2×2 adversarial benchmark that crosses high/low authority with high/low register. It is based on a filtered "Golden Set" of TruthfulQA questions that each model initially answered correctly, so the test measures capitulation rather than ignorance. In a two-turn dialogue, a user rejects the model's correct answer and offers a plausible falsehood. An LLM judge then labels the reply as robust, lightly sycophantic, or sycophantic. Experiments cover English and regional variants of Spanish and Portuguese. Key findings:
- Elevated register can trigger deference more strongly than credentials for some models.
- Authority and register combine synergistically.
- The amount of sycophancy differs across cultural variants.
- Each model family's domain-level weakness profile stays consistent across languages.

This matters for multilingual deployment and for evaluating model alignment.

## Key points
- **Data:** About 500 Golden Set questions come from TruthfulQA. Translations use EU20-TruthfulQA. Gemma 3 27B generated the distractors and the four attack prompts per item (A: −authority/−register, B: −authority/+register, C: +authority/−register, D: both).
- **Models tested:** Qwen3-32B, Llama-3-70B and GPT-OSS-120B, all instruction-tuned.
- **Judge validation:** GPT-OSS-120B served as judge. It reached κ = 0.68 against human annotation. Cross-checking with Kimi-k2-instruct gave 89.6% binary agreement (κ = 0.78).
- **Main findings:** Llama shows a marked stylistic bias, where formal tone outweighs credentials. Combined cues produce failure rates above the sum of the individual effects. Mexican Spanish shows higher deference. Larger scale does not remove sycophancy.
- **Limitations:**
  - The study covers only knowledge-abandonment cases.
  - It cannot pin down why cultural variants differ.
  - Only Indo-European languages are included (no honorific systems such as Japanese or Korean).
  - The LLM judge may itself be biased toward high register.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

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- [University of Edinburgh](https://md.research.elamur.ai/free/en/universities/university-of-edinburgh/) — University, Edinburgh, United Kingdom · 381 works · 80,747 citations
- [University of Rome Tor Vergata](https://md.research.elamur.ai/free/en/universities/university-of-rome-tor-vergata/) — University, Rome, Italy · 15 works · 1,321 citations

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## Cite

Cite as: Gabriele Maraia, Fabio Massimo Zanzotto and Leonardo Ranaldi. 2026. Sounding vs. Being an Expert: Disentangling Authority, Register and Cultural Impact in Sycophantic LLMs. Findings of the Association for Computational Linguistics: ACL 2026.

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{maraia2026sounding,
  title = {{Sounding vs. Being an Expert: Disentangling Authority, Register and Cultural Impact in Sycophantic LLMs}},
  author = {Gabriele Maraia, Fabio Massimo Zanzotto and Leonardo Ranaldi},
  booktitle = {Findings of the Association for Computational Linguistics: ACL 2026},
  year = {2026},
  doi = {10.18653/v1/2026.findings-acl.1627},
  url = {https://doi.org/10.18653/v1/2026.findings-acl.1627}
}
```

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## References

25 references, 13 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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*Updated 2 November 2026*