5 papers · 1 filter
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…
SAGE: Selective Attention-Guided Extraction for Token-Efficient Document Indexing
Xinzhi Wang, Peter Baile Chen, Gerardo Vitagliano +5
Large language models with long context windows can answer complex questions directly from full-length academic, technical, and policy documents, but passing entire documents is of…
SemBench: A Benchmark for Semantic Query Processing Engines
Jiale Lao, Andreas Zimmerer, Olga Ovcharenko +12
We present a benchmark targeting a novel class of systems: semantic query processing engines. Those systems rely inherently on generative and reasoning capabilities of state-of-the…
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…