arXiv:2608. 02616v2 Announce Type: replace-cross Abstract: We present what is, to our knowledge, the first systematic evaluation of OpenAI's Privacy Filter (OPF), a 1.
By Rohith Uppala
arXiv:2608. 02616v1 Announce Type: cross Abstract: We present the first independent, systematic evaluation of OpenAI's Privacy Filter (OPF), a 1.
By Rohith Uppala
arXiv:2606. 24623v1 Announce Type: cross Abstract: Retrieval-Augmented Generation enhances large language models by incorporating external knowledge, but deploying it in sensitive scenarios risks privacy leakage via malicious prompts.
By Yuanhe Zhao, Tianyu Zhang, Huafei Xing, Derek F. Wong, Jianbin Li, Tao Fang
Redakto is a new tool designed to anonymize text before it is processed by large language models (LLMs). It offers state‑of‑the‑art redaction of personally identifiable information (PII) and pseudonymization, accessible via a web interface, REST APIs, and model context protocol hooks. The authors evaluate its performance on legal and medical datasets, showing that anonymized texts retain utility comparable to the originals, enabling LLM tasks without significant loss of effectiveness.
By Saurav Kumar Saha, Tom R\"ohr, Felix Bie{\ss}mann
arXiv:2606. 18782v1 Announce Type: cross Abstract: Large Language Models are increasingly applied to sensitive domains that require redaction of personally identifiable information (PII).
By Sean Brynj\'olfsson, Shashvat Jayakrishnan, Esha Sali, Diptanshu Purwar, Madhav Aggarwal
ASIRF (Agentic Sensitive Information Redaction Framework) is a system that retrieves domain‑specific definitions of sensitive information from a flexible knowledge base at inference time, eliminating the need for retraining when adapting to new domains. It offers two architectures—a three‑call multi‑agent pipeline and a single‑agent variant—and has been evaluated on ten small open‑weight models across eight datasets, including out‑of‑distribution fictional domains. In 68 of 80 model‑domain combinations (85 %), ASIRF’s recall surpasses that of the OpenAI Privacy Filter, with most shortfalls limited to the filter’s training‑distribution domains.
By Sudha Priyadarshini, Mohamed Chahine Ghanem