Behavioral and Representational Evidence of Binomial Ordering Preferences in Large Language Models
Large language models (LLMs) can readily reproduce conventional expressions, yet their ability to model gradient frequency distributions remains underexplored. We investigate this using linguistic binomials, such as men and women, where both word permutations are grammatically valid but exhibit distinct, cross-linguistic variations in conventionality. We formalize binomial ordering as a distributional alignment problem, and construct a multilingual dataset of 600 binomial pairs across 8 languages. With categorical and distributional metrics, we measure and compare the corpus-derived preferences with model-induced ordering probabilities of 6 open-weight LLMs. While models often behaviorall...
| Authors | Zhiqing Yang, Yilun Liu, Yunpu Ma et al. |
|---|---|
| Primary category | cs.CL |
| Published | 19 June 2026 |
| Last updated at source | 19 June 2026 |
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