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Integrity report for RLearner-LLM: Balancing Logical Grounding and Fluency in Large Language Models via Hybrid Direct Preference Optimization

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

arXiv:2605.04539

0Critical
0Advisory
3Detectors run
2026-05-20Last checked

Paper page arXiv integrity.json

Detector runs

ai_meta_artifact completed v1.0.0 · findings 0 · 2026-05-20 11:40:30.311817+00:00
doi_title_agreement completed v1.0.0 · findings 0 · 2026-05-19 23:01:19.717630+00:00
doi_compliance completed v1.0.0 · findings 0 · 2026-05-19 14:20:45.368016+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/2605.04539/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.