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-Based Committee Voting under Incomplete Information
Authors: Aviram Imber, Jonas Israel, Markus Brill, Benny Kimelfeld5076-5083
AAAI 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We investigate approval-based committee voting with incomplete information about the approval preferences of voters. We study the complexity of some fundamental computational problems for a number of classic approval-based committee voting rules |
| Researcher Affiliation | Academia | 1 Technion Israel Institute of Technology, Haifa, Israel 2 Research Group Ef๏ฌcient Algorithms, TU Berlin, Germany |
| Pseudocode | No | The paper describes methods and proofs using narrative text and mathematical notation, but it does not contain any explicitly labeled "Pseudocode" or "Algorithm" blocks. |
| Open Source Code | No | The paper does not contain any statements about releasing source code for the methodologies described, nor does it provide links to any code repositories. |
| Open Datasets | No | This paper is theoretical and focuses on computational complexity analysis. It does not involve the use of datasets for training or evaluation. |
| Dataset Splits | No | This paper is theoretical and focuses on computational complexity analysis. It does not involve empirical validation on datasets, therefore there are no validation splits mentioned. |
| Hardware Specification | No | This paper is theoretical and focuses on computational complexity analysis. It does not describe any empirical experiments, and therefore no specific hardware specifications are mentioned. |
| Software Dependencies | No | This paper is theoretical and focuses on computational complexity analysis. It does not describe any specific software or libraries with version numbers that were used for its research. |
| Experiment Setup | No | This paper is theoretical and focuses on computational complexity analysis. It does not describe empirical experiments, and therefore no specific experimental setup details like hyperparameters or training configurations are provided. |