Newest papers

Bilingual Language Models Capture Cross-Linguistic Influence in Second-Language Reading

Abderrahmane Issam, Irene E. Winther, Stefan L. Frank · 2026 · arXiv

DOI: 10.48550/arXiv.2610.31620 · open-access PDF

Chinese

虽然单语言语言模型(LM)的惊喜被广泛认为是阅读时间的预测器,但它无法捕捉读者第一语言(L1)所形成的非原生(L2)阅读动态。 在这项研究中,我们研究了双语模型中的跨语言转移是否与人类L1驱动的偏见相匹配,而在L2阅读中。

Machine translation (Meta M2M100); the English original follows.

Abstract

While monolingual language model (LM) surprisal is widely established as a predictor of reading times, it cannot capture the non-native (L2) reading dynamics that are shaped by the reader's first language (L1). In this work, we investigate whether the cross-lingual transfer within bilingual models aligns with human L1-driven biases during L2 reading. We evaluate bilingual models on eye-tracking data of readers from 12 diverse L1 backgrounds reading English texts. To isolate L1-specific transfer, we compare bilingual models trained on an L1 that matches the readers' L1 background to both a mono

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