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Probing Latent Colombian Identity Inferences in Qwen2.5-7B with Natural Language Autoencoders

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Computer Science > Computation and Language

arXiv:2607.21774 (cs)
[Submitted on 23 Jul 2026]

Title:Probing Latent Colombian Identity Inferences in Qwen2.5-7B with Natural Language Autoencoders

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Abstract:Large language models may infer demographic attributes from subtle linguistic cues even when those attributes are not explicitly stated. This pilot study examines whether Qwen2.5-7B-Instruct internally represents Colombian identity, socioeconomic status, or stereotype-related information when processing Colombian-Spanish and English prompts. We use Natural Language Autoencoders (NLA) to verbalize residual-stream activations from layer 20 across four positional quartiles per prompt. Our dataset contains 30 prompts arranged as 15 matched Spanish-English pairs, spanning explicit Colombian cues, implicit Colombian cues, and neutral controls. We report descriptive rates and qualitative evidence rather than statistically powered effects, focusing on whether latent nationality or stereotype representations appear before they are verbalized in the model output. This work connects activation-level interpretability with bias evaluation for underrepresented Spanish varieties.
Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2607.21774 [cs.CL]
  (or arXiv:2607.21774v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2607.21774
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Gilber Alexis Corrales Gallego [view email]
[v1] Thu, 23 Jul 2026 19:42:59 UTC (90 KB)
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