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arXiv Computation and Language By Minglu Sun, Lan Chen, Hang Jiang

Knowing Is Not Telling: Identity Ossification in LLM Representations of Trans-border Communities

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The paper investigates how large language models (LLMs) represent nine transborder ethnic communities along China’s southwestern border with mainland Southeast Asia, such as the Sami, Rohingya, and Kurds. It introduces the concept of identity ossification, where LLMs reduce fluid, cross-border identities to a single nation-state narrative, and presents the Transborder Identity Ossification Diagnostic Framework (TIODF) to differentiate between knowledge gaps and narrative framing. Experiments with GPT‑5.1 and DeepSeek‑V3.2 in English and Chinese show that ossification rates vary widely, with DeepSeek‑V3.2’s Chinese responses exhibiting the phenomenon in 62.6% of cases, indicating that narrative framing rather than mere knowledge absence drives the issue.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

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