From the 2 of 11 linked papers with an AI index.
11 papers
"Skill Issues'': Data-Centric Optimization of Lakehouse Agents
Nicole Rose Schneider, Davide Ghilardi, Giacomo Piccinini +1
The paper proposes a data‑centric pipeline that optimizes the skills and environment files used by coding agents on a branching lakehouse, turning evaluation into state verificatio…
Not Your Usual Type(s): Data contracts as types across languages and engines
Aldrin Montana, Colin Marc, Luca Bigon +1
The paper presents an SDK that treats data contracts as typed schemas, enabling consistent validation, documentation, and lineage across multiple programming languages and data eng…
GitLake: Git-for-data for the agentic lakehouse
Weiming Sheng, Jinlang Wang, Manuel Barros +3
We present GitLake, a Git-for-data design for an agent-first lakehouse. The system lifts single-table Iceberg snapshots into lakehouse-wide commits, branches, and merges, letting a…
Test-Time Optimization of Physical Query Plans with LLMs
Mehmet Hamza Erol, Xiangpeng Hao, Federico Bianchi +3
Traditional query optimization relies on cost-based optimizers that estimate execution cost (e.g., runtime, memory, and I/O) using predefined heuristics and statistical models. Imp…
Building a Correct-by-Design Lakehouse. Data Contracts, Versioning, and Transactional Pipelines for Humans and Agents
Weiming Sheng, Jinlang Wang, Manuel Barros +3
Lakehouses are now the default substrate for analytics and AI, but they remain fragile under concurrent, untrusted change: schema mismatches often surface only at runtime, developm…
Querying Everything Everywhere All at Once: Supervaluationism for the Agentic Lakehouse
Jacopo Tagliabue
Agentic analytics is turning the lakehouse into a multi-version system: swarms of (human or AI) producers materialize competing pipelines in data branches, while (human or AI) cons…