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..
Proportionality Guarantees in Elections with Interdependent Issues
Authors: Markus Brill, Evangelos Markakis, Georgios Papasotiropoulos, Jannik Peters
IJCAI 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Our findings indicate that the conditional case poses additional challenges and differs significantly from the unconditional one, both in terms of proportionality guarantees and computational complexity. |
| Researcher Affiliation | Collaboration | 1University of Warwick, Coventry, UK 2Athens University of Economics and Business, Athens, Greece 3Input Output Global (IOG) 4TU Berlin, Berlin, Germany |
| Pseudocode | No | The paper describes algorithms (Conditional Proportional Approval Voting and Conditional Method of Equal Shares) but does not include structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not include an explicit statement about releasing source code for the methodology or a link to a code repository. |
| Open Datasets | No | The paper is theoretical and focuses on mathematical proofs and analysis of voting rules; it does not use or reference any datasets for training or evaluation. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical experiments with dataset splits (training, validation, test). |
| Hardware Specification | No | The paper is theoretical and does not describe any specific hardware used for experiments. |
| Software Dependencies | No | The paper is theoretical and does not specify any ancillary software or library versions used for implementation or experiments. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup with specific hyperparameters or system-level training settings. |