Integrity report for PSK@EEUCA 2026: Fine-Tuning Large Language Models with Synthetic Data Augmentation for Multi-Class Toxicity Detection in Gaming Chat

A machine-verified record of the checks Pith has run against this paper: detector runs, findings, signed bundle events, and canonical identifiers.

arXiv:2605.07201

0Critical

0Advisory

4Detectors run

2026-05-20Last checked

Paper page arXiv integrity.json

Detector runs

claim_evidence completed v1.0.0 · findings 0 · 2026-05-20 11:22:03.322613+00:00

ai_meta_artifact completed v1.0.0 · findings 0 · 2026-05-20 06:34:58.580361+00:00

doi_title_agreement completed v1.0.0 · findings 0 · 2026-05-19 17:01:19.604427+00:00

doi_compliance completed v1.0.0 · findings 0 · 2026-05-19 12:00:52.337498+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/2605.07201/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.