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cs.DB2026
Robust Hierarchical Structures for Agentic Document Analysis
Ruiying Ma, Yiming Lin, Aditya G. Parameswaran
Large Language Models (LLMs) enable us to better understand text documents, including PDFs and Word documents. However, LLMs, as well as more modern LLM agents, i.e., those with to…
cs.DB2026
Bolt-on, Verifiable Provenance for LLM-Powered Data Processing
Yiming Lin, Sepanta Zeighami, Aditya G. Parameswaran
Large Language Models (LLMs) are powerful tools for processing data. However, LLMs are also complex black-boxes, returning answers to queries on data, without any indication for wh…
cs.DB2026
Scout: Scalable Document Extraction via Data Similarity
Yiming Lin, Chiyu Hao, Shreya Shankar +1
Extracting values from large document collections powers data analysis across many domains. Frontier LLMs extract such values accurately, but processing an entire collection with o…