# CyrillicQA: The Influence of Phonetically Encoded Secret Language on LLM Performance

arXiv: https://arxiv.org/abs/2608.21462 · HTML: https://mlsanity.com/paper/2608.21462/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 9 of its 19 references that are in the map.
- First posted on arXiv 20 Aug 2026.

## Builds on (most cited first, 9 of 9)

- [TruthfulQA: Measuring How Models Mimic Human Falsehoods](https://mlsanity.com/paper/2109.07958/) (2021)
- [Quantifying the Dialect Gap and its Correlates Across Languages](https://mlsanity.com/paper/2310.15135/) (2023)
- [Assessing Dialect Fairness and Robustness of Large Language Models in Reasoning Tasks](https://mlsanity.com/paper/2410.11005/) (2024)
- [Beneath the Surface of Consistency: Exploring Cross-lingual Knowledge Representation Sharing in LLMs](https://mlsanity.com/paper/2408.10646/) (2024)
- [Evaluating Dialect Robustness of Language Models via Conversation Understanding](https://mlsanity.com/paper/2405.05688/) (2024)
- [Large Language Models Discriminate Against Speakers of German Dialects](https://mlsanity.com/paper/2509.13835/) (2025)
- [Against All Odds: Overcoming Typology, Script, and Language Confusion in Multilingual Embedding Inversion Attacks](https://mlsanity.com/paper/2408.11749/) (2024)
- [Exploring the Role of Transliteration in In-Context Learning for Low-resource Languages Written in Non-Latin Scripts](https://mlsanity.com/paper/2407.02320/) (2024)
- [IYKYK: Using language models to decode extremist cryptolects](https://mlsanity.com/paper/2506.05635/) (2025)

## Abstract (arXiv)

Due to the selection of their training data, large language models (LLMs) perform best on standard-language inputs from languages using the Latin alphabet with large speaker populations, while disadvantaging other language varieties. Nevertheless, they can also be a versatile tool for preserving precisely such endangered languages. But do they also possess the necessary creativity and capacity for abstraction to decode phonetically encoded language the same way humans do?