Properties of Position Matrices and Their Elections
Authors: Niclas Boehmer, Jin-Yi Cai, Piotr Faliszewski, Austen Z. Fan, Łukasz Janeczko, Andrzej Kaczmarczyk, Tomasz Wąs
AAAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We complement our theoretical findings with experiments. |
| Researcher Affiliation | Academia | Technische Universität Berlin, University of Wisconsin-Madison, AGH University, Pennsylvania State University |
| Pseudocode | No | The paper describes a 'naive approach' for sampling in Section 3.3, outlining steps in paragraph text, but it does not present this or any other method in a structured pseudocode or algorithm block. |
| Open Source Code | Yes | The code for the experiments is available at: https://github.com/Project-PRAGMA/Position-Matrices-AAAI-2023. |
| Open Datasets | Yes | For our experiments, we use an 8x80 dataset that resembles those of Szufa et al. (2020), Boehmer et al. (2021b), and Boehmer et al. (2022). |
| Dataset Splits | No | The paper states, 'Specifically, we considered elections with either 4 or 8 candidates and either 40, 80, or 160 voters,' but it does not provide specific percentages, absolute counts, or a methodology for training, validation, or test dataset splits. |
| Hardware Specification | No | The paper does not specify any particular hardware (e.g., GPU/CPU models, memory specifications) used for running the experiments. |
| Software Dependencies | No | The paper mentions using 'a python module called permanent' and provides a URL for it, but it does not specify version numbers for this or any other software dependencies. |
| Experiment Setup | Yes | We performed the following experiment: (i) For each election from the 8x80 dataset we computed its position matrix, (ii) using the naive sampler, we generated 100 pairs of elections that realize it, and, (iii) for each pair of elections, we computed their isomorphic swap distance. |