Sounding vs. Being an Expert: Disentangling Authority, Register and Cultural Impact in Sycophantic LLMs

Gabriele Maraia, Fabio Massimo Zanzotto, Leonardo Ranaldi


Abstract
Large Language Models (LLMs) have been shown to exhibit sycophancy, a tendency to align with user assertions even when they conflict with facts. We frame sycophancy as a sociolinguistic phenomenon, disentangling two distinct drivers of credibility: explicit authority (credentials) and implicit authority (linguistic register). We introduce the Sycophancy Matrix, an adversarial evaluation framework that isolates these variables. Using a controlled subset of TruthfulQA, we evaluate open-weight models across English, Spanish, and Portuguese variants. Our findings reveal that models often conflate high register with truthfulness: for some architectures, sophisticated tone triggers deference more effectively than explicit expertise. Furthermore, we observe statistically significant variability across cultural variants of Spanish and Portuguese, supporting the hypothesis that LLMs internalise language-specific sociolinguistic norms and that sycophancy is not a purely technical deficit but an emergent property of multilingual training and alignment. Finally, we identify stable sycophancy fingerprints–domain-specific vulnerability profiles that persist across languages–suggesting that alignment artefacts are intrinsic to model families rather than linguistic context.
Anthology ID:
2026.findings-acl.1627
Volume:
Findings of the Association for Computational Linguistics: ACL 2026
Month:
July
Year:
2026
Address:
San Diego, California, United States
Editors:
Maria Liakata, Viviane P. Moreira, Jiajun Zhang, David Jurgens
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
32492–32508
Language:
URL:
https://preview.aclanthology.org/ingest-acl/2026.findings-acl.1627/
DOI:
Bibkey:
Cite (ACL):
Gabriele Maraia, Fabio Massimo Zanzotto, and Leonardo Ranaldi. 2026. Sounding vs. Being an Expert: Disentangling Authority, Register and Cultural Impact in Sycophantic LLMs. In Findings of the Association for Computational Linguistics: ACL 2026, pages 32492–32508, San Diego, California, United States. Association for Computational Linguistics.
Cite (Informal):
Sounding vs. Being an Expert: Disentangling Authority, Register and Cultural Impact in Sycophantic LLMs (Maraia et al., Findings 2026)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingest-acl/2026.findings-acl.1627.pdf
Checklist:
 2026.findings-acl.1627.checklist.pdf