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; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1]
Optimizing Positional Scoring Rules for Rank Aggregation
Authors: Ioannis Caragiannis, Xenophon Chatzigeorgiou, George Krimpas, Alexandros Voudouris
AAAI 2017 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We study this fundamental problem from a theoretical point of view and present positive and negative complexity results. Furthermore, we complement our theoretical findings with experiments on real-world and synthetic data. |
| Researcher Affiliation | Academia | Ioannis Caragiannis University of Patras EMAIL Xenophon Chatzigeorgiou University of Patras EMAIL George A. Krimpas University of Patras EMAIL Alexandros A. Voudouris University of Patras EMAIL |
| Pseudocode | No | The paper describes algorithms in prose and uses a figure for illustration (Figure 1), but it does not contain a formally labeled 'Pseudocode' or 'Algorithm' block with structured steps. |
| Open Source Code | No | The paper does not provide any explicit statement about releasing source code or a link to a code repository for the methodology described. |
| Open Datasets | Yes | The set of constraints were defined using population data for the 48 countries from en.wikipedia.org and cost of living index data from numbeo.com. |
| Dataset Splits | No | The paper does not specify training, validation, or test dataset splits for its experiments. The research focuses on finding an optimal scoring rule rather than training a machine learning model with traditional data splits. |
| Hardware Specification | No | The paper does not describe the specific hardware used to run its experiments (e.g., CPU, GPU models, or cloud resources). |
| Software Dependencies | No | The paper does not provide specific version numbers for any software components, libraries, or solvers used in the experiments. |
| Experiment Setup | Yes | For synthetic profiles with BT and PL agents, the simulation was repeated 500 times; the values shown here are averages... This rather disappointing outcome, together with the fact that d is small, forced us to consider scoring vectors with discretized scores (e.g., which are multiples of 0.05 or 0.02) in order to come up with approximations of the optimal scoring rule. |