[2512.02418] Leveraging Large Language Models to Bridge Cross-Domain Transparency in Stablecoins

Computer Science > Cryptography and Security arXiv:2512.02418 (cs) [Submitted on 2 Dec 2025 (v1), last revised 1 Apr 2026 (this version, v3)] Title:Leveraging Large Language Models to Bridge Cross-Domain Transparency in Stablecoins Authors:Yuexin Xiang, Yuchen Lei, Yuanzhe Zhang, Qin Wang, Tsz Hon Yuen, Andreas Deppeler, Jiangshan Yu View a PDF of the paper titled Leveraging Large Language Models to Bridge Cross-Domain Transparency in Stablecoins, by Yuexin Xiang and 6 other authors View PDF HTML (experimental) Abstract:Stablecoins such as USDT and USDC aspire to peg stability by coupling issuance controls with reserve attestations. In practice, however, transparency remains fragmented across heterogeneous data sources, with key evidence about circulation, reserves, and disclosure dispersed across records that are difficult to connect and interpret jointly. We introduce a large language model (LLM)-based automated framework for bridging cross-domain transparency in stablecoins by aligning issuer disclosures with observable circulation evidence. First, we propose an integrative framework using LLMs to parse documents, extract salient financial indicators, and semantically align reported statements with corresponding market and issuance metrics. Second, we integrate multi-chain issuance records and disclosure documents within a model context protocol (MCP) framework that standardizes LLM access to both quantitative market data and qualitative disclosure narratives. This fram...