Papers with English-centric reasoning

2 papers
Mind the Gap: Multilingual Divide in LLM Bias Detection and Reasoning (2026.acl-srw)

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Challenge: Large Language Models (LLMs) are increasingly deployed in multilingual settings . but most bias evaluation remains English-centric and ignores how bias manifests within reasoning .
Approach: They evaluate large language models with supervised fine-tuning and preference optimization . they find that bias varies substantially across languages, with consistent degradation in non-English settings .
Outcome: The proposed model improves in English, Dutch, Spanish, and Turkish using the MBBQ benchmark.
Do LLMs Capture Embodied Cognition and Cultural Variation? Cross-Linguistic Evidence from Demonstratives (2026.acl-long)

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Challenge: a new study examines whether large language models acquire embodied cognition and cultural conventions from training data . demonstratives are a natural lens for evaluating linguistic phenomena that reflect cultural variation . aaron e. duan and j. nà: "the complexity of the language model is a major challenge for LLMs"
Approach: They introduce demonstratives as a probe for grounded knowledge by analyzing 6,400 responses from 320 native speakers.
Outcome: The proposed model fails to understand proximal–distal contrast and shows no cultural differences . the proposed model is a new probe for evaluating embodied cognition and cultural conventions .

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