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].
Random Walk Decay Centrality
Authors: Tomasz Wąs, Talal Rahwan, Oskar Skibski2197-2204
AAAI 2019 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We provide an axiomatic characterization and show that the new centrality is closely related to Page Rank. More in detail, we show that replacing only one axiom, called Lack of Self Impact, with another one, called Edge Swap, results in the new axiomatization of Page Rank. |
| Researcher Affiliation | Academia | 1Institute of Informatics, University of Warsaw, Poland 2Computer Science, New York University, Abu Dhabi, UAE |
| Pseudocode | No | No pseudocode or algorithm blocks were found. |
| Open Source Code | No | No statement or link regarding open-source code for the described methodology was found. |
| Open Datasets | No | The paper primarily presents theoretical analysis and uses illustrative examples (Figure 1, 2, 3) rather than formally stated datasets with access information for training. |
| Dataset Splits | No | The paper does not describe experiments with datasets, and therefore no dataset split information (training, validation, test) is provided. |
| Hardware Specification | No | The paper is theoretical and does not describe experiments, therefore no hardware specifications are mentioned. |
| Software Dependencies | No | The paper is theoretical and does not describe experiments, therefore no software dependencies are mentioned. |
| Experiment Setup | No | The paper is theoretical and illustrates concepts with examples, but does not provide specific experimental setup details such as hyperparameters for empirical evaluation. |