LAVA: Logic-Aware Validation and Augmentation Framework for Large-Scale Financial Document Auditing
Financial document validation in production, such as payroll auditing, tax compliance, and loan underwriting, demands exceptional accuracy, consistency, and reproducibility under strict enterprise constraints. In practice, documents arrive with heterogeneous layouts and formats, semantically rich and context-dependent content, and embedded business rules that current pipelines struggle to process reliably. We introduce LAVA (Logic-Aware Validation and Augmentation), a modular, backbone-agnostic pipeline built on multimodal large language models, that integrates a four-stage design: document-rule retrieval, layout-preserving information extraction, auxiliary metadata enrichment, and audita...
| Authors | Ruoqi Shu, Xuhui Wang, Isaac Wang et al. |
|---|---|
| Primary category | cs.AI |
| Published | 17 August 2026 |
| Last updated at source | 17 August 2026 |
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