vip (R package): papers linking to it

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to vip (R package) (https://CRAN.R-project.org/package=vip), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

Key findings#

7 papers in the tracked journals link to vip (R package) in their Crossref records, the first in 2023; most of them (3) in 2025.
By category: AI (5), Information Systems (1) and Finance (1); the journals with the most are Business & Information Systems Engineering (1), Expert Systems with Applications (1) and Neural Computing and Applications (1).

By year#

20232025

Papers linking to vip (R package) by publication year
Year	Papers
2023	3
2024	1
2025	3

Journals#

Journals whose papers link to vip (R package) most
Journal	Papers
Business & Information Systems Engineering	1
Expert Systems with Applications	1
Neural Computing and Applications	1
Knowledge and Information Systems	1
European Actuarial Journal	1

Papers linking to vip (R package), most cited first
Published	Title	Journal	Authors	Citations	Link
2023-07-27	Explaining machine learning models with interactive natural language conversations using TalkToModel	Nature Machine Intelligence	Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju et al.	125	cites it
2023-02-23	A data mining framework for reporting trends in the predictive contribution of factors related to educational achievement	Expert Systems with Applications	Rogério Luiz Cardoso Silva Filho, Kellyton dos Santos Brito, Paulo J. L. Adeodato	18	cites it
2023-11-01	Detection of interacting variables for generalized linear models via neural networks	European Actuarial Journal	Yevhen Havrylenko, Julia Heger	5	cites it
2025-11-04	ChronoSHAP: Revealing temporal patterns from transformers and LTSF-linear models in time series forecasting	Knowledge-Based Systems	Alberto Miño Calero, Adil Rasheed, Anastasios M. Lekkas	5	cites it
2024-12-13	Analyzing feature importance with neural-network-derived trees	Neural Computing and Applications	Ernesto Vieira-Manzanera, Miguel Angel Patricio, Antonio Berlanga et al.	3	cites it
2025-05-30	Context-Based Subvariant Discovery for Process Mining via Machine Learning	Business & Information Systems Engineering	Fabian Gwinner, Myriam Schaschek, Axel Winkelmann	2	cites it
2025-05-05	Numerical dependency analysis (NDA): a new method for estimating the statistical dependence (not correlation) of two variables	Knowledge and Information Systems	Abolfazl Zanghaei, Hassan Doosti, Ali Ameri et al.	0	cites it

How this is measured#

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

Cite this page

Scholar4AI. (2026). vip (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-vip

@misc{scholar4ai-code-cran-vip,
  author = {{Scholar4AI}},
  title = {vip (R package): papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/cran-vip}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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