2 citations · 3 across the 8 of their papers we have counts for
8 papers
ELT-Bench-Verified: Benchmark Quality Issues Underestimate AI Agent Capabilities
Christopher Zanoli, Andrea Giovannini, Tengjun Jin +2
Constructing Extract-Load-Transform (ELT) pipelines is a labor-intensive data engineering task and a high-impact target for AI automation. On ELT-Bench, the first benchmark for end…
Accelerating Approximate Analytical Join Queries over Unstructured Data with Statistical Guarantees
Yuxuan Zhu, Tengjun Jin, Chenghao Mo +1
Analytical join queries over unstructured data are increasingly prevalent in data analytics. Applying machine learning (ML) models to label every pair in the cross product of table…
Human-Level Text-to-SQL via Reinforcement Learning on Verified Data, Without Pipeline Engineering
Yuxuan Zhu, Tengjun Jin, Yoojin Choi +1
Translating natural language questions to SQL queries (Text-to-SQL) is a long-standing problem in database research. Recent efforts have focused on improving accuracy by building i…
Pervasive Annotation Errors Break Text-to-SQL Benchmarks and Leaderboards
Tengjun Jin, Yoojin Choi, Yuxuan Zhu +1
Researchers have proposed numerous text-to-SQL techniques to streamline data analytics and accelerate the development of data-driven applications. To compare these techniques and s…
Holistic Agent Leaderboard: The Missing Infrastructure for AI Agent Evaluation
Sayash Kapoor, Benedikt Stroebl, Peter Kirgis +28
AI agents have been developed for complex real-world tasks from coding to customer service. But AI agent evaluations suffer from many challenges that undermine our understanding of…
Establishing Best Practices for Building Rigorous Agentic Benchmarks
Yuxuan Zhu, Tengjun Jin, Yada Pruksachatkun +22
Benchmarks are essential for quantitatively tracking progress in AI. As AI agents become increasingly capable, researchers and practitioners have introduced agentic benchmarks to e…
ELT-Bench: An End-to-End Benchmark for Evaluating AI Agents on ELT Pipelines
Tengjun Jin, Yuxuan Zhu, Daniel Kang
Practitioners are increasingly turning to Extract-Load-Transform (ELT) pipelines with the widespread adoption of cloud data warehouses. However, designing these pipelines often inv…
PilotDB: Database-Agnostic Online Approximate Query Processing with A Priori Error Guarantees (Technical Report)
Yuxuan Zhu, Tengjun Jin, Stefanos Baziotis +3
After decades of research in approximate query processing (AQP), its adoption in the industry remains limited. Existing methods struggle to simultaneously provide user-specified er…