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].
Metric-Distortion Bounds under Limited Information
Authors: Ioannis Anagnostides, Dimitris Fotakis, Panagiotis Patsilinakos
JAIR 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | From an experimental standpoint, we present several empirical findings on real-life voting applications, comparing the scoring systems employed in practice with a mechanism explicitly minimizing (metric) distortion. Interestingly, for our case studies, we find that the winner in the actual competition is typically the candidate who minimizes the distortion. |
| Researcher Affiliation | Academia | Ioannis Anagnostides EMAIL Carnegie Mellon University, Pittsburgh, USA Dimitris Fotakis EMAIL National Technical University of Athens, Greece Panagiotis Patsilinakos EMAIL National Technical University of Athens, Greece |
| Pseudocode | Yes | Algorithm 1: Domination Root Input: Set of candidates C, Pairwise comparison oracle O; Output: Winner w C; 1. Initialize S := C; 2. Construct arbitrarily a set Π of S/2 pairings from S; 3. For every {a, b} Π remove O(a, b) from S; 4. If |S| = 1 return w S; otherwise, continue from step 2; |
| Open Source Code | Yes | Our code is publicly available at https://github.com/ioannis Anagno/Voting-Metric Distortion. |
| Open Datasets | Yes | For our experiments we used a dataset from Kaggle. |
| Dataset Splits | No | The paper analyzes "real-life voting applications" (Eurovision, Formula One), which typically involve complete historical data for analysis rather than train/test/validation splits for model training. The text does not specify any dataset splits. |
| Hardware Specification | No | The induced LPs in Minimax-LP will be solved via the Gurobi software (Gurobi Optimization, 2021). No other specific hardware details are provided for the experiments. |
| Software Dependencies | Yes | The induced LPs in Minimax-LP will be solved via the Gurobi software (Gurobi Optimization, 2021). |
| Experiment Setup | Yes | Eurovision employs a specific positional scoring system which works as follows. Every country assigns 12 points to its highest preference, 10 points to its second-highest preference, and from 8 to 1 points to each of its next 8 preferences, respectively... The scoring rule employed in F1 assigns to the first 10 drivers the points 25, 18, 15, 12, 10, 8, 6, 4, 2, 1, respectively... |