Notice: This website is continuously updated as new conference proceedings and journal volumes are published. Consequently, the figures presented here may differ from those reported in our publications.
A brief overview of our methodology is provided on the Methods page, along with references to publications documenting our approach and links to the code and data used in each study.
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.
Strategic Voting and Strategic Candidacy
Authors: Markus Brill, Vincent Conitzer
AAAI 2015 | Venue PDF | LLM Run Details | Input Tokens: 17,643 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 3,563 Total number of tokens produced by the LLM (including reasoning/thinking tokens) for this paper's analysis.
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We study the computational complexity of the latter case and show that computing the set of sophisticated outcomes is NP-complete. Due to space constraints, some proofs are omitted. |
| Researcher Affiliation | Academia | Markus Brill and Vincent Conitzer Department of Computer Science Duke University Durham, NC 27708, USA EMAIL |
| Pseudocode | No | The paper does not contain any pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | No | The paper does not provide any statements or links regarding the availability of open-source code for the described methodology. |
| Open Datasets | No | The paper is theoretical and does not involve training models on datasets. It discusses theoretical concepts and examples. |
| Dataset Splits | No | The paper is theoretical and does not involve experimental validation with dataset splits. It provides proofs and theoretical analyses. |
| Hardware Specification | No | The paper is theoretical and does not involve computational experiments that would require specific hardware specifications. |
| Software Dependencies | No | The paper is theoretical and does not mention any specific software dependencies with version numbers for reproducibility of computational work. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup details such as hyperparameters or training configurations. |