Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Body-Decoupled Grounding via Solving: A Novel Approach on the ASP Bottleneck
Authors: Viktor Besin, Markus Hecher, Stefan Woltran
IJCAI 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We demonstrate the feasibility of this new method experimentally by comparing it to standard ASP technology in terms of grounding size, grounding time and total runtime. |
| Researcher Affiliation | Academia | 1TU Wien, Vienna, Austria 2University of Potsdam, Potsdam, Germany |
| Pseudocode | Yes | Figure 1: Body-decoupled grounding procedure R for a given tight non-ground program Π, which creates a disjunctive ground program. |
| Open Source Code | Yes | 1Our system including supplemental material of this work is publicly available at https://github.com/viktorbesin/newground. |
| Open Datasets | Yes | For answering the hypotheses, we use crafted (random) and applicable ASP competition instances. Note that competition instances are not designed to run into grounding bottlenecks. |
| Dataset Splits | No | The paper describes generating instances and using ASP competition instances but does not specify any explicit train/validation/test dataset splits, percentages, or cross-validation methods. |
| Hardware Specification | No | The paper states: "We limit main memory (RAM) to 16GB and overall runtimes (grounding & solving) to 1800s." This mentions memory limits but does not specify CPU models, GPU models, or other detailed hardware components used for running the experiments. |
| Software Dependencies | Yes | The system newground is written in Python3 and uses, among others, the API and of clingo 5.5 and its ability to efficiently parse logic programs via syntax trees. |
| Experiment Setup | Yes | We limit main memory (RAM) to 16GB and overall runtimes (grounding & solving) to 1800s. |