most citedDRAMA: Unifying Data Retrieval and Analysis for Open-Domain Analytic Queries

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

BI-Agent and BI-Bench: Towards Automating End-to-End Business Intelligence

Chuxuan Hu, Yeye He, Penny Zhou +3

Business intelligence (BI) is a cornerstone of enterprise decision-making and is widely used by enterprise users in software such as Power BI and Tableau. In traditional BI workflo…

cs.DB2026

SODIUM: From Open Web Data to Queryable Databases

Chuxuan Hu, Philip Li, Maxwell Yang +1

During research, domain experts often ask analytical questions whose answers require integrating data from a wide range of web sources. Thus, they must spend substantial effort sea…

cs.DB2025★ 2 cited

DRAMA: Unifying Data Retrieval and Analysis for Open-Domain Analytic Queries

Chuxuan Hu, Maxwell Yang, James Weiland +3

Manually conducting real-world data analyses is labor-intensive and inefficient. Despite numerous attempts to automate data science workflows, none of the existing paradigms or sys…

cs.CL2025

REPRO-Bench: Can Agentic AI Systems Assess the Reproducibility of Social Science Research?

Chuxuan Hu, Liyun Zhang, Yeji Lim +3

Assessing the reproducibility of social science papers is essential for promoting rigor in research processes, but manual assessment is costly. With recent advances in agentic AI s…

cs.DB2025

LEAP: LLM-powered End-to-end Automatic Library for Processing Social Science Queries on Unstructured Data

Chuxuan Hu, Austin Peters, Daniel Kang

Social scientists are increasingly interested in analyzing the semantic information (e.g., emotion) of unstructured data (e.g., Tweets), where the semantic information is not nativ…