21 citations · 31 across the 12 of their papers we have counts for
4 papers · 1 filter
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…
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…
MinerU-Popo: Universal Post-Processing Model for Structured Document Parsing
Bangrui Xu, Ziyang Miao, Xuanhe Zhou +7
VLM-based OCR models have become the de facto choice for document parsing, as they can accurately extract page-level elements (e.g., paragraphs within individual pages) together wi…
Can AI Agents Answer Your Data Questions? A Benchmark for Data Agents
Ruiying Ma, Shreya Shankar, Ruiqi Chen +7
However, building reliable data agents remains difficult because real enterprise data is fragmented across many heterogeneous database systems, with duplicated and inconsistent dat…