Best Student Paper Award at ICLP 2025 for Automated Hybrid Grounding research
We're excited to announce that the paper “Automated Hybrid Grounding Using Structural and Data-Driven Heuristics” received the Best Student Paper Award at ICLP2025!

We’re excited to announce that Alexander Beiser (TU Wien - CAIML PhD Researcher), Markus Hecher (Univ. Artois, CNRS), and Stefan Woltran (TU Wien) won the Best Student Paper award at 41st International Conference on Logic Programming (ICLP 2025) in Rende, Italy on Automated Hybrid Grounding Using Structural and Data-Driven Heuristics.
The paper advances the long-standing “grounding bottleneck” in Answer Set Programming (ASP). The method decides—based on the rule structure, instance data, and grounding size estimation —when to use body-decoupled grounding and when to rely on standard bottom-up grounding.
About the venue: ICLP is the flagship conference of the logic programming community. The 2025 edition took place at the University of Calabria, Rende (Italy), 12–19 September 2025.
Abstract
The grounding bottleneck poses one of the key challenges that hinders the widespread adoption of Answer Set Programming in industry. Hybrid Grounding is a step in alleviating the bottleneck by combining the strength of standard bottom-up grounding with recently proposed techniques where rule bodies are decoupled during grounding. However, it has remained unclear when hybrid grounding shall use body-decoupled grounding and when to use standard bottom-up grounding. In this paper, we address this issue by developing automated hybrid grounding: we introduce a splitting algorithm based on data-structural heuristics that detects when to use body-decoupled grounding and when standard grounding is beneficial. We base our heuristics on the structure of rules and an estimation procedure that incorporates the data of the instance. The experiments conducted on our prototypical implementation demonstrate promising results, which show an improvement on hard-to-ground scenarios, whereas on hard-to-solve instances we approach state-of-the-art performance.
arXiv link: https://arxiv.org/abs/2507.17493
venue link: https://iclp25.demacs.unical.it/