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..
Approval with Runoff
Authors: Théo Delemazure, Jérôme Lang, Jean-François Laslier, M. Remzi Sanver
IJCAI 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We analyse the outcome of these rules on one-dimensional Euclidean profiles (Section 5), and move on to applying the rules on real data (Section 6). |
| Researcher Affiliation | Academia | 1CNRS, Universit e Paris-Dauphine, Universit e PSL, LAMSADE 2CNRS, Paris School of Economics, Universit e PSL |
| Pseudocode | No | The paper provides mathematical definitions and formulas for the rules, but it does not include pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described, nor does it explicitly state that code is released or available. |
| Open Datasets | Yes | We used approval ballot datasets from different sources: Datasets from several cities conducted during the 2017 French presidential election [Bouveret et al., 2019]... Two datasets of a poster competition held at the San Sebastian Summer School on Computational Social Choice7... 7Available on www.preflib.org |
| Dataset Splits | No | The paper mentions using datasets for analysis but does not specify any training, validation, or test dataset splits. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware used to run its simulations or analyses. |
| Software Dependencies | No | The paper defines mathematical voting rules and their properties. It does not mention any specific software or libraries, along with their version numbers, that were used for implementation or analysis. |
| Experiment Setup | Yes | We sampled 20,000 voters and 1,000 candidates. Again, every voter approves candidates at distance d. For each d and α we compute the two finalists and observed their positions on the line. The first selected finalist is always the closest to the center. |