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..
Acquiring Integer Programs from Data
Authors: Mohit Kumar, Stefano Teso, Luc De Raedt
IJCAI 2019 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our empirical evaluation shows that ARNOLD can acquire models for a number of realistic benchmark problems. (3) An extensive empirical analysis on a number of integer programs, showing that ARNOLD can acquire good quality programs from a handful of examples. |
| Researcher Affiliation | Academia | Mohit Kumar , Stefano Teso and Luc De Raedt KU Leuven EMAIL |
| Pseudocode | Yes | Algorithm 1 The ARNOLD search algorithm. |
| Open Source Code | Yes | Our code is available at github.com/mohit KULeuven/arnold |
| Open Datasets | Yes | To this end, we used ARNOLD for learning 10 satisfaction/satisficing Mini Zinc [Nethercote et al., 2007] benchmark integer programs1, detailed in Table 2. 1From github.com/Mini Zinc/benchmarks and from hakank.org/minizinc. |
| Dataset Splits | Yes | Next, we split the dataset into five folds of 25 solutions each and fed ARNOLD with n {1, 2, 10, 25} random solutions from one fold as training set, while using the union of the other four folds for performance evaluation. |
| Hardware Specification | No | The paper does not provide specific hardware details such as CPU/GPU models, memory, or cloud instance types used for running experiments. It mentions 'Runtime' but not the underlying hardware. |
| Software Dependencies | No | The paper mentions using 'Mini Zinc [Nethercote et al., 2007]' and 'Gecode solver [Schulte et al., 2006]' but does not provide specific version numbers for these or other software dependencies. |
| Experiment Setup | Yes | The parameters used were (s, p) = (1, 1), (1, 2), (1, 3), (2, 1), (3, 1), which are large enough to capture the majority of the benchmark problems, and n = 1, 5, 10, 25. |