collaborators

11 papers

cs.HC2026

Who's Keeping Score? Interactive Steering of LLM-Powered Scoring with Attune

Bhavya Chopra, Meng Chen, Rebecca Dang +5

Large language models (LLMs) are increasingly used to score text records at scale (e.g., rating candidate resumes on a 1-5 scale). However, existing LLM-powered approaches do not a…

cs.DB2026

Semantic Data Processing with Holistic Data Understanding

Youran Sun, Sepanta Zeighami, Bhavya Chopra +2

Semantic operators have increasingly become integrated within data systems to enable processing data using Large Language Models (LLMs). Despite significant recent effort in improv…

cs.DB2026

Multi-Objective Agentic Rewrites for Unstructured Data Processing

Lindsey Linxi Wei, Shreya Shankar, Sepanta Zeighami +3

One year ago, we open-sourced DocETL, a declarative system for LLM-powered data processing that, as of March 2026, has 3.7K GitHub stars and users across domains (e.g., journalism,…

cs.DB2026

Can AI Agents Answer Your Data Questions? A Benchmark for Data Agents

Ruiying Ma, Shreya Shankar, Ruiqi Chen +7

Users across enterprises increasingly rely on AI agents to query their data through natural language. However, building reliable data agents remains difficult because real-world da…

cs.DB2026

Arming Data Agents with Tribal Knowledge

Shubham Agarwal, Asim Biswal, Sepanta Zeighami +3

Natural language to SQL (NL2SQL) translation enables non-expert users to query relational databases through natural language. Recently, NL2SQL agents, powered by the reasoning capa…

cs.DB2026

Task Cascades for Efficient Unstructured Data Processing

Shreya Shankar, Sepanta Zeighami, Aditya Parameswaran

Modern database systems allow users to query or process unstructured text or document columns using LLM-powered functions. Users can express an operation in natural language (e.g.,…