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..
Multiwinner Voting with Possibly Unavailable Candidates
Authors: Markus Brill, Hayrullah Dindar, Jonas Israel, Jérôme Lang, Jannik Peters, Ulrike Schmidt-Kraepelin
AAAI 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we formalize the mentioned model and adapt the concept of a query policy (Boutilier et al. 2014) to multiwinner elections. Such a policy queries candidates for their availability, with the constraint that a queried candidate has to be included in the selection once they signal their availability. We then study common approval-based committee (ABC) rules and investigate whether these rules admit a safe query policy, i.e., a policy that only queries candidates that are guaranteed to be included in an optimal selection whenever they are available, whatever the other available candidates are. We show that under a mild technical assumption a necessary and sufficient condition for a rule to admit a safe query policy is sequentiality (to be formally defined later). |
| Researcher Affiliation | Academia | 1 Research Group Efficient Algorithms, Technische Universit at Berlin, Germany 2 Department of Computer Science, University of Warwick, Coventry, UK 3 CNRS, Universit e Paris-Dauphine, PSL, LAMSADE, France EMAIL, EMAIL, EMAIL, EMAIL, EMAIL, EMAIL |
| Pseudocode | No | The paper describes algorithms and procedures but does not present them in a formalized pseudocode block or a clearly labeled algorithm section. |
| Open Source Code | No | Omitted proofs can be found in the full version of this paper (available at https://www.markus-brill.de/). This link is for omitted proofs, not for the source code of the methodology described in the paper. |
| Open Datasets | No | This is a theoretical paper and does not involve training models on datasets. Therefore, no information about public datasets for training is provided. |
| Dataset Splits | No | This is a theoretical paper and does not involve data splits for validation or training. Therefore, no information about training/validation/test splits is provided. |
| Hardware Specification | No | This is a theoretical paper that does not involve computational experiments requiring specific hardware. Therefore, no hardware specifications are mentioned. |
| Software Dependencies | No | This is a theoretical paper that does not involve computational experiments requiring specific software dependencies with version numbers. Therefore, no software dependency details are provided. |
| Experiment Setup | No | This is a theoretical paper and does not involve empirical experiments with specific setups or hyperparameters. Therefore, no experimental setup details are provided. |