Abstract
Recently, the development of foundation models has led to significant advances in the ability of artificial intelligence (AI) to generate multimodal content such as text and images. However, specialized industrial scenarios such as finance, which require high levels of security and compliance, pose challenges for the application of generative AI due to its uncontrollability. To address this issue, we propose FinGuard, a multimodal AI-generated content (AIGC) guardrail specifically designed for financial scenarios. We provide detailed definitions of the general quality, financial compliance, and security dimensions of AIGC, and implement the evaluation and inspection of multimodal AIGC including text and images. Our proposed FinGuard has been applied to a financial marketing application serving hundreds of millions of users.
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CITATION STYLE
Du, W., Li, Q., Zhou, J., Ding, X., Wang, X., Zhou, Z., & Liu, J. (2023). FinGuard: A Multimodal AIGC Guardrail in Financial Scenarios. In Proceedings of the 5th ACM International Conference on Multimedia in Asia, MMAsia 2023. Association for Computing Machinery, Inc. https://doi.org/10.1145/3595916.3626351
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