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..
New Compilation Languages Based on Restricted Weak Decomposability
Authors: Petr Illner
AAAI 2025 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our experiments demonstrate that nw DNNF circuits are suitable for computing MPEs in two-layer Bayesian networks (BNs) with large domains. |
| Researcher Affiliation | Academia | Petr Illner Department of Theoretical Computer Science and Mathematical Logic, Faculty of Mathematics and Physics Charles University, Czech Republic EMAIL |
| Pseudocode | No | We refer the curious reader to (Illner and Kuˇcera 2024) for a more detailed description of Bella and the pseudocode, where the methods compute Components and compute New Cut were changed as described below. |
| Open Source Code | Yes | 1https://github.com/Illner/Bella Compiler |
| Open Datasets | No | We implemented Bels2 to (randomly) generate and convert such BNs into CNF formulae using the encodings mentioned in this paper. |
| Dataset Splits | No | Ten instances were created for each density. Since the compilers are randomised, each instance was compiled three times, and the given results are averages. |
| Hardware Specification | Yes | The experiments3 were performed on a Linux machine (Debian 11) using an AMD EPYC 7543 2.8GHz processor and 512 Gi B of RAM. |
| Software Dependencies | No | The experiments3 were performed on a Linux machine (Debian 11) using an AMD EPYC 7543 2.8GHz processor and 512 Gi B of RAM. The time-out (resp. memory-out) was set to two/six hours (resp. 16 GB). |
| Experiment Setup | Yes | The time-out (resp. memory-out) was set to two/six hours (resp. 16 GB). The following compilers were considered: Bella, D44 (the randomised variant introduced by Illner and Kuˇcera (2024) was used), C2D5, and Sharp SAT-TD6. Ten instances were created for each density. Since the compilers are randomised, each instance was compiled three times, and the given results are averages. |