Papers by Spencer Romo
IDP Accelerator: Agentic Document Intelligence from Extraction to Compliance Validation (2026.acl-demo)
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Md Mofijul Islam, Md Sirajus Salekin, Joe King, Priyashree Roy, Vamsi Thilak Gudi, Spencer Romo, Akhil Nooney, Bob Strahan, Boyi Xie, Diego A. Socolinsky
| Challenge: | Large Language Models (LLMs) are inadequate for extracting structured insights from unstructured documents. |
| Approach: | They propose a framework enabling agentic AI for end-to-end document intelligence with four key components: DocSplit, configurable Extraction Module, and Rule Validation Module. |
| Outcome: | The proposed framework achieves 98% classification accuracy, 80% reduced processing latency, and 77% lower operational costs over legacy baselines. |
DocSplit: A Comprehensive Benchmark Dataset and Evaluation Approach for Document Packet Recognition and Splitting (2026.acl-industry)
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Md Mofijul Islam, Md Sirajus Salekin, Nivedha Balakrishnan, Vincil C. Bishop III, Niharika Jain, Spencer Romo, Bob Strahan, Boyi Xie, Diego A. Socolinsky
| Challenge: | Document understanding in real-world applications often requires processing heterogeneous, multi-page document packets containing multiple documents stitched together. |
| Approach: | They propose to use document packet splitting to improve document understanding in real-world applications. |
| Outcome: | The proposed datasets and evaluation metrics provide a systematic framework for advancing document understanding capabilities essential for legal, financial, healthcare, and other document-intensive domains. |