DiRAFT: Privacy-Aware Financial Transcript Synthesis from Aggregate Discourse Priors

arXiv:2610.40938v1 Announce Type: new Abstract: Using customer conversations to train and evaluate financial language models raises confidentiality concerns because non-public financial facts can remain after direct identifiers are masked. Synthetic transcripts offer an alternative data source, but

arXiv cs.AIMontag 06:00 · 02.11.1 Min. Lesezeit