---
title: "Who cites IncogniText: Privacy-enhancing — 8 citing papers"
description: "8 papers of the Elamur Research library cite «IncogniText: Privacy-enhancing Conditional Text Anonymization via LLM-based Private Attribute…"
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---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [IncogniText: Privacy-enhancing Conditional Text…](https://md.research.elamur.ai/free/en/papers/frikha-2025-incognitext-privacy-enhancing-conditional-text/) / cited by

# Who cites «IncogniText: Privacy-enhancing Conditional Text Anonymization via LLM-based Private Attribute Randomization»

8 papers of our library cite it (of the 149,439 whose bibliographies we read) · 4 with a page here, the most cited first · [← back to «IncogniText: Privacy-enhancing Conditional Text Anonymization via LLM-based Private Attribute Randomization»](https://md.research.elamur.ai/free/en/papers/frikha-2025-incognitext-privacy-enhancing-conditional-text/)

1. **[PrivacyRestore: Privacy-Preserving Inference in Large Language Models via Privacy Removal and Restoration](https://md.research.elamur.ai/free/en/papers/zeng-2025-privacyrestore-privacy-preserving-inference-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziqian Zeng, Jianwei Wang, Junyao Yang, et al.*2025 · 13 citations*
2. **[Adaptive Text Anonymization: Learning Privacy-Utility Trade-offs via Prompt Optimization](https://md.research.elamur.ai/free/en/papers/loiseau-2026-adaptive-text-anonymization-learning-privacy/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Gabriel Loiseau, Damien Sileo, Damien Riquet, et al.*2026 · 2 citations*
3. **[Private Seeds, Public LLMs: Realistic and Privacy-Preserving Synthetic Data Generation](https://md.research.elamur.ai/free/en/papers/ma-2026-private-seeds-public-llms-realistic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qian Ma, Sarah Rajtmajer*2026*
4. **[Subject-level Inference for Realistic Text Anonymization Evaluation](https://md.research.elamur.ai/free/en/papers/oh-2026-subject-level-inference-realistic-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Myeong Seok Oh, Dong-Yun Kim, Hanseok Oh, et al.*2026*

4 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/frikha-2025-incognitext-privacy-enhancing-conditional-text/) — IncogniText: Privacy-enhancing Conditional Text Anonymization via LLM-based Private Attribute Randomization