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..
Poll-Confident Voters in Iterative Voting
Authors: Anaëlle Wilczynski2205-2212
AAAI 2019 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments are given for testing the practical convergence of the dynamics and the quality of their outcomes. |
| Researcher Affiliation | Academia | Ana elle Wilczynski Universit e Paris-Dauphine, PSL, CNRS, LAMSADE, Paris, France EMAIL |
| Pseudocode | Yes | Algorithm 1: Margin rebalance on two candidates |
| Open Source Code | No | The paper does not provide any explicit statement or link indicating that the source code for the methodology is openly available. |
| Open Datasets | No | We conduct experiments over 10,000 generated instances with 100 voters and 10 candidates, under impartial culture for the preferences and random Erd os and R enyi[1959] s graphs (see Fig. 2). |
| Dataset Splits | No | The paper describes generating instances for experiments but does not explicitly provide details about training/validation/test dataset splits in the conventional sense. |
| Hardware Specification | No | The paper does not explicitly describe the hardware used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific version numbers for any software dependencies used in the experiments. |
| Experiment Setup | Yes | We examine unanimous thresholds of value 1, 5 and 10 and heterogeneous ones uniformly distributed over the voters with values in [1..5] or [1..10]. |