Integrity report for Be Fair! Can Machine Learning Engineering Agents Adhere to Fairness Constraints?

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

arXiv:2606.04971 · pith:2026:3SVRIF7RSGZHQAQBZHG2DF5PYL

0Critical

0Advisory

6Detectors run

2026-06-05Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

claim_evidence completed v1.0.0 · findings 0 · 2026-06-05 03:29:13.940841+00:00

external_links completed v1.0.0 · findings 0 · 2026-06-04 23:32:16.166679+00:00

shingle_duplication skipped v0.1.0 · findings 0 · 2026-06-04 13:50:32.586379+00:00

citation_quote_validity skipped v0.1.0 · findings 0 · 2026-06-04 05:51:06.348987+00:00

cited_work_retraction completed v1.0.0 · findings 0 · 2026-06-04 04:27:18.869259+00:00

ai_meta_artifact skipped v1.0.0 · findings 0 · 2026-06-04 01:35:37.316550+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/3SVRIF7RSGZHQAQBZHG2DF5PYL/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.