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.
Reconfiguring Shortest Paths in Graphs
Authors: Kshitij Gajjar, Agastya Vibhuti Jha, Manish Kumar, Abhiruk Lahiri9758-9766
AAAI 2022 | Venue PDF | LLM Run Details | Input Tokens: 19,137 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 2,808 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 | In this paper, we undertake a theoretical study of the reconfiguration problem on shortest paths, known as the Shortest Path Reconfiguration problem (abbreviated as SPR), introduced by (Kaminski, Medvedev, and Milanic 2010). |
| Researcher Affiliation | Academia | 1 National University of Singapore, Singapore 2 Ecole polytechnique f ed erale de Lausanne, Switzerland 3 Ben-Gurion University of the Negev, Israel 4 Ariel University, Israel |
| Pseudocode | Yes | Algorithm 1: SPR for weakly modular graphs; Algorithm 2: SPR for Boolean hypercubes |
| Open Source Code | No | The paper focuses on theoretical contributions (algorithms, complexity proofs) and does not mention releasing any source code for its methods. |
| Open Datasets | No | The paper is theoretical and does not involve the use of datasets for training or any other purpose. |
| Dataset Splits | No | The paper is theoretical and does not involve the use of datasets, hence no validation splits are discussed. |
| Hardware Specification | No | The paper is theoretical and does not describe any experiments, therefore no hardware specifications are mentioned. |
| Software Dependencies | No | The paper is theoretical and does not describe any experiments or implementations that would require specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup or hyperparameters. |