Integer Quantization of Graph Neural Networks for Real-Time FPGA Track Finding
- DOI
- 10.48550/arxiv.2609.28144
- Published
- 2026
- Container
- Not recorded
- Publisher
- arXiv
- Open access
- no
Credibility signals
limited evidence Score 41/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- cautionDOI registered: No matching Crossref record was present in this response.
- cautionDOI resolves: No matching Crossref record was present in this response.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- supportingPublication license: A publication license was supplied: http://arxiv.org/licenses/nonexclusive-distrib/1.0/. Presence improves reuse transparency, not research validity.
- cautionPublication version: Identified as a preprint; peer review and later versions may change the record.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.48550/arxiv.2609.28144,
title = {Integer Quantization of Graph Neural Networks for Real-Time FPGA Track Finding},
author = {Cardini, Andrea and Leguina, Pelayo and Aller, Elena and Folgueras, Santiago},
year = {2026},
doi = {10.48550/arxiv.2609.28144},
url = {https://doi.org/10.48550/arxiv.2609.28144}
}RIS
TY - JOUR TI - Integer Quantization of Graph Neural Networks for Real-Time FPGA Track Finding AU - Cardini, Andrea AU - Leguina, Pelayo AU - Aller, Elena AU - Folgueras, Santiago PY - 2026 DO - 10.48550/arxiv.2609.28144 UR - https://doi.org/10.48550/arxiv.2609.28144 ER -
APA
Andrea, C., Pelayo, L., Elena, A., & Santiago, F. (2026). Integer Quantization of Graph Neural Networks for Real-Time FPGA Track Finding. https://doi.org/10.48550/arxiv.2609.28144
Source records
- datacite · retrieved 2026-09-26T04:54:46.234Z