NAC: Noise-Adaptive Correction for Robust Graph Neural Networks toward Trusted Graph Computing

Hwan Kim, Jiha Kim, Seunghyun Park, Hyunhee Park

Open source

DOI: 10.21203/rs.3.rs-9264474/v1
Published: 2026-04-23
Container: Not recorded
Publisher: Springer Science and Business Media LLC
Open access: unknown

Credibility signals

uncertain Score 60/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

supportingDOI registered: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
supportingDOI resolves: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
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. Source: DOAJ; license: CC0
not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
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. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
cautionPublication version: Identified as a preprint; peer review and later versions may change the record. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
supportingMetadata completeness: All 6 scored descriptive metadata groups are present. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.21203/rs.3.rs-9264474/v1,
  title = {NAC: Noise-Adaptive Correction for Robust Graph Neural Networks toward Trusted Graph Computing},
  author = {Hwan Kim and Jiha Kim and Seunghyun Park and Hyunhee Park},
  year = {2026},
  doi = {10.21203/rs.3.rs-9264474/v1},
  url = {https://doi.org/10.21203/rs.3.rs-9264474/v1}
}

RIS

TY  - JOUR
TI  - NAC: Noise-Adaptive Correction for Robust Graph Neural Networks toward Trusted Graph Computing
AU  - Hwan Kim
AU  - Jiha Kim
AU  - Seunghyun Park
AU  - Hyunhee Park
PY  - 2026
DO  - 10.21203/rs.3.rs-9264474/v1
UR  - https://doi.org/10.21203/rs.3.rs-9264474/v1
ER  -

APA

Kim, H., Kim, J., Park, S., & Park, H. (2026). NAC: Noise-Adaptive Correction for Robust Graph Neural Networks toward Trusted Graph Computing. https://doi.org/10.21203/rs.3.rs-9264474/v1

Source records

crossref · retrieved 2026-09-26T13:54:08.673Z