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Integrity report for Learning from Fine-Grained Visual Discrepancies: Mitigating Multimodal Hallucinations via In-Context Visual Contrastive Optimization

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

arXiv:2605.31312 · pith:2026:NJVJJDOV5EPCDZXOBD3HPG3GIR

0Critical
0Advisory
5Detectors run
2026-06-04Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

claim_evidence completed v1.0.0 · findings 0 · 2026-06-04 15:29:03.509536+00:00
citation_quote_validity skipped v0.1.0 · findings 0 · 2026-06-01 01:50:47.966164+00:00
shingle_duplication skipped v0.1.0 · findings 0 · 2026-06-01 01:50:16.298267+00:00
ai_meta_artifact skipped v1.0.0 · findings 0 · 2026-06-01 01:35:04.428192+00:00
cited_work_retraction completed v1.0.0 · findings 0 · 2026-06-01 01:25:41.874771+00:00

Findings

No public integrity findings for this paper.

Signed record

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