4 papers
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…
Rethinking Dataset Discovery with DataScout
Rachel Lin, Bhavya Chopra, Wenjing Lin +3
Dataset Search -- the process of finding appropriate datasets for a given task -- remains a critical yet under-explored challenge in data science workflows. Assessing dataset suita…
TARGET: Benchmarking Table Retrieval for Generative Tasks
Xingyu Ji, Parker Glenn, Aditya G. Parameswaran +1
The data landscape is rich with structured data, often of high value to organizations, driving important applications in data analysis and machine learning. Recent progress in repr…