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 [1].
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. |