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Integrity report for Domain-Adaptable Reinforcement Learning for Code Generation with Dense Rewards

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

arXiv:2605.21180 · pith:2026:MQ3A5LAB6YIO755XZDSVDP7LZC

0Critical
0Advisory
6Detectors run
2026-05-25Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

doi_title_agreement completed v1.0.0 · findings 0 · 2026-05-25 06:02:41.469975+00:00
doi_compliance completed v1.0.0 · findings 0 · 2026-05-25 06:01:59.398144+00:00
claim_evidence completed v1.0.0 · findings 0 · 2026-05-25 05:43:42.921576+00:00
cited_work_retraction completed v1.0.0 · findings 0 · 2026-05-21 06:23:14.770366+00:00
citation_quote_validity skipped v0.1.0 · findings 0 · 2026-05-21 01:50:22.177257+00:00
ai_meta_artifact skipped v1.0.0 · findings 0 · 2026-05-21 01:33:50.121225+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/MQ3A5LAB/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.