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 Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
The Distortion of Threshold Approval Matching
Authors: Mohamad Latifian, Alexandros A. Voudouris
IJCAI 2024 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We show tight bounds on distortion of deterministic and randomized matching algorithms that are functions of the number of threshold utility levels. |
| Researcher Affiliation | Academia | 1University of Toronto, Canada 2University of Essex, UK EMAIL, EMAIL |
| Pseudocode | No | The paper describes mechanisms using mathematical notation and prose (e.g., Definition 1, Definition 4), but it does not include structured pseudocode blocks or sections explicitly labeled "Algorithm" or "Pseudocode". |
| Open Source Code | No | No statement explicitly indicates that source code for the described methodology is available, nor is a specific repository link provided. |
| Open Datasets | No | This is a theoretical paper focused on deriving mathematical bounds and properties of mechanisms; it does not use or refer to any publicly available datasets for training or evaluation. |
| Dataset Splits | No | This is a theoretical paper and does not involve empirical validation on datasets, thus it does not provide details about training, validation, or test data splits. |
| Hardware Specification | No | This is a theoretical paper that focuses on mathematical analysis and algorithm design; it does not mention any specific hardware used for experiments. |
| Software Dependencies | No | This is a theoretical paper and does not describe any specific software dependencies or their version numbers required to replicate empirical experiments. |
| Experiment Setup | No | This is a theoretical paper and does not include details about an experimental setup, such as hyperparameters or system-level training settings. |