aiqbench analysis
PragAlign introduces a novel architecture that decouples context comprehension from selective clarification, demonstrating superior performance in multilingual reply assistance across Chinese and Japanese cultural contexts. By validating these methods against native speaker judgments, the study provides critical insights for building AI systems capable of nuanced cross-cultural communication rather than just literal translation. This research advances the field of computational linguistics by addressing the specific challenge of culturally situated appropriateness in automated dialogue generation.
PragAlign: Evidence-Sensitive Reply Assistance Across Chinese and Japanese Appropriateness Judgments
arXiv:2608.26700v1 Announce Type: new Abstract: Reply assistance in multilingual settings requires linguistic competence and culturally situated judgments of appropriateness. We present PragAlign, which separates context reading from selective clarification, and evaluate it alongside Direct and Rule. Nine native Chinese speakers judged Chinese materials, while three native Japanese speakers judged matched Japanese versions. In the Chinese evaluation, PragAlign received significantly better ranks than both baselines. In the Japanese evaluation, Direct had the lowest mean rank, PragAlign had the highest top-rank rate, and the omnibus difference was not significant. The groups selected the same top condition in 5 of 10 scenarios, including four shared PragAlign selections. The results identify shared and language-specific judgment patterns and inform reply assistance designed to support linguistic and cultural understanding.
Abstract:Reply assistance in multilingual settings requires linguistic competence and culturally situated judgments of appropriateness. We present PragAlign, which separates context reading from selective clarification, and evaluate it alongside Direct and Rule. Nine native Chinese speakers judged Chinese materials, while three native Japanese speakers judged matched Japanese versions. In the Chinese evaluation, PragAlign received significantly better ranks than both baselines. In the Japanese evaluation, Direct had the lowest mean rank, PragAlign had the highest top-rank rate, and the omnibus difference was not significant. The groups selected the same top condition in 5 of 10 scenarios, including four shared PragAlign selections. The results identify shared and language-specific judgment patterns and inform reply assistance designed to support linguistic and cultural understanding.
Computation and Language (cs.CL)
arXiv:2608.26700 [cs.CL]
(or arXiv:2608.26700v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2608.26700 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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