Generative AI for Multimedia Communication: Recent Advances, An Information-Theoretic Framework, and Future Opportunities
Jin, Yili Liu, Xue Liu, Jiangchuan
Jin, Yili
Liu, Xue
Liu, Jiangchuan
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Supervisor
Department
Machine Learning
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Type
Conference proceeding
Date
2025
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Language
English
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Abstract
Recent breakthroughs in generative artificial intelligence (AI) are transforming multimedia communication. This paper systematically reviews key recent advancements across generative AI for multimedia communication, emphasizing transformative models like diffusion and transformers. However, conventional information-theoretic frameworks fail to address semantic fidelity, critical to human perception. We propose an innovative semantic information-theoretic framework, introducing semantic entropy, mutual information, channel capacity, and rate-distortion concepts specifically adapted to multimedia applications. This framework redefines multimedia communication from purely syntactic data transmission to semantic information conveyance. We further highlight future opportunities and critical research directions. We chart a path toward robust, efficient, and semantically meaningful multimedia communication systems by bridging generative AI innovations with information theory. This exploratory paper aims to inspire a semantic-first paradigm shift, offering a fresh perspective with significant implications for future multimedia research.
Citation
Y. Jin, X. Liu, and J. Liu, “Generative AI for Multimedia Communication: Recent Advances, An Information-Theoretic Framework, and Future Opportunities,” Proceedings of the 33rd ACM International Conference on Multimedia, pp. 12237–12246, Oct. 2025, doi: 10.1145/3746027.3758149
Source
MM '25: Proceedings of the 33rd ACM International Conference on Multimedia
Conference
The 33rd ACM International Conference on Multimedia
Keywords
Generative AI, Multimedia Communication, Information Theory
Subjects
Source
The 33rd ACM International Conference on Multimedia
Publisher
Association for Computing Machinery