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].
Complexity of Manipulation with Partial Information in Voting
Authors: Palash Dey, Neeldhara Misra, Y. Narahari
IJCAI 2016 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Our results show that several of the voting rules that are easy to manipulate in the complete information setting become intractable when the manipulators know only partial votes. Our hardness results often hold even when very little information is missing, or in other words, even when the instances are quite close to the complete information setting. Our overall conclusion is that computational hardness continues to be a valid obstruction to manipulation, in the context of a more realistic model. |
| Researcher Affiliation | Academia | Indian Institute of Science, Bangalore Indian Institute of Technology, Gandhinagar |
| Pseudocode | No | The paper describes algorithms and reductions in prose and mathematical notation but does not include structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not mention providing open-source code for the described methodology. |
| Open Datasets | No | The paper is theoretical and does not describe experiments using datasets. |
| Dataset Splits | No | The paper is theoretical and does not describe experiments using datasets, thus no validation split information is provided. |
| Hardware Specification | No | The paper describes theoretical results and does not mention any hardware specifications. |
| Software Dependencies | No | The paper describes theoretical results and does not mention specific software dependencies with version numbers. |
| Experiment Setup | No | The paper describes theoretical results and does not include details on an experimental setup or hyperparameters. |