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..
Parameterized Complexity of Kidney Exchange Revisited
Authors: Úrsula Hébert-Johnson, Daniel Lokshtanov, Chinmay Sonar, Vaishali Surianarayanan
IJCAI 2024 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We show that Kidney Exchange is FPT parameterized by the number of vertex types. On the other hand, we show W[1]-hardness with respect to ω. We also design a randomized 4tn O(1)-time algorithm parameterized by t, the number of patients helped, significantly improving upon the previous state of the art, which was 161tn O(1). |
| Researcher Affiliation | Academia | Ursula H ebert-Johnson, Daniel Lokshtanov, Chinmay Sonar and Vaishali Surianarayanan UC Santa Barbara EMAIL |
| Pseudocode | No | The paper describes algorithms conceptually and refers to existing algorithms (e.g., 'reduce the problem to an ILP', 'randomized algorithm'), but does not include any explicit pseudocode blocks or algorithm listings. |
| Open Source Code | No | The paper does not provide any statement or link indicating the availability of open-source code for the described methodology. |
| Open Datasets | No | The paper is theoretical and focuses on algorithm design and complexity analysis; it does not describe experiments using a dataset for training. |
| Dataset Splits | No | The paper is theoretical and does not describe any empirical experiments, thus no dataset validation splits are provided. |
| Hardware Specification | No | The paper is theoretical and does not describe any experiments, therefore no hardware specifications are provided. |
| Software Dependencies | No | The paper is theoretical and does not describe any experiments with specific software dependencies or versions. |
| Experiment Setup | No | The paper is theoretical and does not describe any experiments, therefore no experimental setup details like hyperparameters or training configurations are provided. |