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RedactionBench

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arXiv:2606. 18782v1 Announce Type: new Abstract: Large Language Models are increasingly applied to sensitive domains that require redaction of personally identifiable information (PII).

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Authors: Sean Brynj\'olfsson, Shashvat Jayakrishnan, Esha Sali, Diptanshu Purwar, Madhav Aggarwal
Released: 2026-06-18 (21d ago)
Topic: Related to current project
Relation to my work: Read next because RedactionBench overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: text, persona, eval, source, line, rate, extraction, compare. Source: arxiv cs.CL (NLP).
arXiv: 2606.18782

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