2 citations · 3 across the 12 of their papers we have counts for
8 papers · 1 filter
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…
The Time is Here for Just-in-Time Systems: Challenges and Opportunities
Shu Liu, Alexander Krentsel, Shubham Agarwal +8
Core systems like key-value stores have historically taken years to build, and are designed to be general so as to amortize cost across deployments, paying a significant performanc…
Inductive Deductive Synthesis: Enabling AI to Generate Formally Verified Systems
Shubham Agarwal, Alexander Krentsel, Shu Liu +10
AI agents increasingly excel at generating, testing, and refining code. However, they fall short on tasks requiring formal guarantees of full coverage that testing alone cannot pro…
PLOP: Cost-Based Placement of Semantic Operators in Hybrid Query Plans
Qiuyang Mang, Yufan Xiang, Hangrui Zhou +5
Recent database systems have introduced semantic operators that leverage large language models (LLMs) to filter, join, and project over structured data using natural language predi…
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…
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…
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…
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.,…