Integrity report for Best Practices for Data-Efficient Modeling in NLG:How to Train Production-Ready Neural Models with Less Data
A machine-verified record of the checks Pith has run against this paper: detector runs, findings, signed bundle events, and canonical identifiers.
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Paper page arXiv integrity.json bundle.json
Detector runs
Findings
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Signed record
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