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This is a Experimental Study study.

Research on Innovation of Artificial Intelligence-Driven Translation and Communication Models

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The proposed model demonstrates significant gains in semantic understanding and domain-specific terminology adaptation.
Evaluation results indicate enhanced multilingual translation performance and efficiency in AI-driven systems.
Challenges such as cultural transfer and low-resource language support remain, emphasizing areas for future work.
The study underscores the need for cross-modal integration to optimize translation technologies for effective communication.

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Systematic review reveals strengths of AI-based translation technologies, suggesting improvements in multilingual performance.

韩成 Han Cheng (2025) studied this question.

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