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..
Preserving Condorcet Winners under Strategic Manipulation
Authors: Sirin Botan, Ulle Endriss5202-5210
AAAI 2021 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Our main result in this respect is an impossibility theorem that establishes that no tournament solution satisfying a very weak decisiveness requirement can provide such a guarantee. |
| Researcher Affiliation | Academia | Sirin Botan and Ulle Endriss Institute for Logic, Language and Computation, University of Amsterdam EMAIL |
| Pseudocode | No | The paper provides theoretical definitions, theorems, and proofs, but does not include any pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | No | The paper does not provide any concrete access to source code for the methodology described. |
| Open Datasets | No | This is a theoretical paper that does not involve empirical training with publicly available datasets. The paper constructs abstract pro๏ฌles for theoretical analysis. |
| Dataset Splits | No | This is a theoretical paper and does not involve empirical experiments that require validation dataset splits. |
| Hardware Specification | No | This is a theoretical paper and does not mention any specific hardware used for running experiments. |
| Software Dependencies | No | This is a theoretical paper and does not specify any software dependencies with version numbers for experimental replication. |
| Experiment Setup | No | This is a theoretical paper and does not include details about an experimental setup, hyperparameters, or training configurations. |