PRX Part 4: Our Data Strategy

Data Is Better Together: A Look Back and Forward

Efficient Table Pre-training without Real Data: An Introduction to TAPEX

Reviving our data foundations is the most disruptive step to data maturity

The article argues that for small‑to‑medium enterprises, the most disruptive yet essential step toward data maturity is to rebuild or strengthen a solid knowledge foundation layer. It stresses that this initiative must be evidence‑backed and minimally disruptive to current processes, and it proposes a low‑impact data strategy that adapts to evolving data flows. The authors emphasize that knowledge graph techniques will become indispensable in AI‑powered enterprises if designed modularly, dynamically, and cross‑functionally.

Valid Inference with Synthetic Data via Task Exchangeability

arXiv:2606. 13629v1 Announce Type: cross Abstract: There is a proliferation of work arguing for the use of synthetic data in scientific research.

Synthetic data: save money, time and carbon with open source

SyGra: The One-Stop Framework for Building Data for LLMs and SLMs

Intelligence is Free, Now What? <br> Data Systems for, of, and by Agents

government of the people, by the people, for the people ... &nbsp;&nbsp;&nbsp;&nbsp;&mdash; Abraham Lincoln, Gettysburg Address (1863) The cost of AI is dropping rapidly.

AutoSynthData: Generating Training Data for Enterprise Agents

Creating Impactful Autonomous Driving Datasets: A Strategic Guide from Research Gap to Benchmark

arXiv:2607. 00710v1 Announce Type: cross Abstract: Well-designed autonomous driving datasets have fundamentally shaped research progress, yet existing literature primarily describes what datasets contain rather than how to strategically design impactful ones.

Property-Driven Synthetic Data Engineering for Data-Scarce Software Systems: Reflections from the Breast Cancer Domain

arXiv:2607. 06133v1 Announce Type: cross Abstract: Modern software systems increasingly depend on data for analysis, prediction, testing, and decision-making.

Goal-Driven Reasoning in DatalogMTL with Magic Sets

arXiv:2412. 07259v5 Announce Type: replace Abstract: DatalogMTL is a powerful rule-based language for temporal reasoning.

BAP-SQL: Budget-Aware Observation Planning for Agentic Text-to-SQL

arXiv:2608. 02876v1 Announce Type: new Abstract: Tool-using agents do not merely consume observations: their actions determine what arrives next.