---
title: "Who cites Layer-Aware Representation — 9 citing papers"
description: "9 papers of the Elamur Research library cite «Layer-Aware Representation Filtering: Purifying Finetuning Data to Preserve LLM Safety…"
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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/) / [Layer-Aware Representation Filtering: Purifying…](https://md.research.elamur.ai/free/en/papers/li-2025-layer-aware-representation-filtering-purifying/) / cited by

# Who cites «Layer-Aware Representation Filtering: Purifying Finetuning Data to Preserve LLM Safety Alignment»

9 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 «Layer-Aware Representation Filtering: Purifying Finetuning Data to Preserve LLM Safety Alignment»](https://md.research.elamur.ai/free/en/papers/li-2025-layer-aware-representation-filtering-purifying/)

1. **[The Unintended Trade-off of AI Alignment: Balancing Hallucination Mitigation and Safety in LLMs](https://md.research.elamur.ai/free/en/papers/mahmoud-2026-unintended-trade-off-ai-alignment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Omar Mahmoud, Ali Khalil, Thommen George Karimpanal, et al.*2026 · 2 citations*
2. **[Be Your Own Red Teamer: Safety Alignment via Self-Play and Reflective Experience Replay](https://md.research.elamur.ai/free/en/papers/wang-2026-be-your-own-red-teamer/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Wang, Yanting Wang, Hao Li, et al.*2026 · 1 citation*
3. **[Safeguarding LLM Fine-tuning via Push-Pull Distributional Alignment](https://md.research.elamur.ai/free/en/papers/wang-2026-safeguarding-llm-fine-tuning-push/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haozhong Wang, Zhuo Li, Yibo Yang, et al.*2026*
4. **[SGT: Securing Open-Source LLMs Against Malicious Fine-tuning via Safety Guidance Trigger](https://md.research.elamur.ai/free/en/papers/shin-2026-sgt-securing-open-source-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sunguk Shin, Fangzhao Wu, Byung-Jun Lee, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/li-2025-layer-aware-representation-filtering-purifying/) — Layer-Aware Representation Filtering: Purifying Finetuning Data to Preserve LLM Safety Alignment