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This paper proposes a cross-linguistic transfer learning approach for detecting Alzheimer's Disease from speech across multiple languages, achieving F1 scores of 82% and supporting real-time screening applications.
This paper investigates brain-LLM alignment across English, Chinese, and French using fMRI data and multiple LLMs, finding that training-language dominance and typological distance, not an inherent English advantage, drive alignment patterns.
This paper analyzes the Huitongguanxi Huayiyiyu, a series of multilingual glossaries from the Ming dynasty, as a structured cross-linguistic transcription system that used Chinese characters to represent non-Chinese languages, revealing how Chinese phonological categories were flexibly extended for phonetic approximation.
This paper investigates how politeness and impoliteness in user prompts affect LLM responses across three languages and five major models, finding that politeness effects are language- and model-dependent rather than universal. The authors release PLUM, a multilingual corpus of 1,500 human-validated prompts with politeness annotations, and assess response quality using eight factors.