From the 1 of 7 linked papers with an AI index.
7 papers
Carnot: Interpretable, Interactive, and Optimized Execution of Deep Research Queries
Matthew Russo, Yash Agarwal, Tianyu Li +5
Enterprises increasingly seek to query data lakes using natural language via AI-driven tools like semantic operators or deep research agents. However, the latter operates as an opa…
AutoSLO: Practical Latency SLOs on Cloud Data Warehouses -- Extended Version
Markos Markakis, Tim Kraska
AutoSLO is a framework that automatically manages compute clusters in cloud data warehouses to meet latency service-level objectives while reducing resource waste, using proactive…
Recursive Language Models
Alex L. Zhang, Tim Kraska, Omar Khattab
We study allowing large language models (LLMs) to process arbitrarily long prompts through the lens of inference-time scaling. We propose Recursive Language Models (RLMs), a genera…
KramaBench: A Benchmark for AI Systems on Data-to-Insight Pipelines over Data Lakes
Eugenie Lai, Gerardo Vitagliano, Ziyu Zhang +16
Discovering insights from a real-world data lake potentially containing unclean, semi-structured, and unstructured data requires a variety of data processing tasks, ranging from ex…
Abacus: A Cost-Based Optimizer for Semantic Operator Systems
Matthew Russo, Chunwei Liu, Sivaprasad Sudhir +4
LLMs enable an exciting new class of data processing applications over large collections of unstructured documents. Several new programming frameworks have enabled developers to bu…
Deep Research is the New Analytics System: Towards Building the Runtime for AI-Driven Analytics
Matthew Russo, Tim Kraska
With advances in large language models (LLMs), researchers are creating new systems that can perform AI-driven analytics over large unstructured datasets. Recent work has explored…