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Large language model–based translation systems are reshaping multilingual information access as interactive, prompt-driven interfaces that restructure the cognitive, social, and institutional conditions of cross-language information seeking. This theory-building review argues this shift constitutes an emergent mode of information behavior warranting a distinct theoretical construct: Prompt-Mediated Multilingual Information Access. Prompt-Mediated Multilingual Information Access is defined as a mode of information access in which a user employs iteratively refined natural-language prompts to elicit artificial intelligence–mediated translation, transformation, or synthesis of information across a language boundary in response to an evolving, goal-directed information need. Drawing on literature spanning library and information science, human–computer interaction, and cross-language information retrieval, this study (1) positions Prompt-Mediated Multilingual Information Access as a distinct construct extending cross-language information retrieval, interactive information retrieval, and conversational search; (2) presents a five-layer socio-cognitive mediation model; (3) develops five falsifiable theoretical propositions linking prompt literacy, trust calibration, language asymmetry, and institutional mediation; (4) operationalizes prompt literacy as a socio-cognitive competence across four dimensions; (5) provides exploratory empirical evidence through an analysis of 1602 real-world interactions (WildChat-1M) and a 16-model large language model benchmark; and (6) identifies implications for library and information science practice and multilingual artificial intelligence governance.
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Kalem et al. (2026) studied this question.
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