---
title: "Who cites Certified Robustness to Text — 33 citing papers"
description: "33 papers of the Elamur Research library cite «Certified Robustness to Text Adversarial Attacks by Randomized [MASK]», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/zeng-2023-certified-robustness-text-adversarial-attacks/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/zeng-2023-certified-robustness-text-adversarial-attacks/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Certified Robustness to Text Adversarial Attacks…](https://md.research.elamur.ai/free/en/papers/zeng-2023-certified-robustness-text-adversarial-attacks/) / cited by

# Who cites «Certified Robustness to Text Adversarial Attacks by Randomized [MASK]»

33 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 «Certified Robustness to Text Adversarial Attacks by Randomized MASK»](https://md.research.elamur.ai/free/en/papers/zeng-2023-certified-robustness-text-adversarial-attacks/)

1. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 237 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
2. **[A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-safety-trustworthiness-large-language/) [Artificial Intelligence Review](https://md.research.elamur.ai/free/en/venues/artificial-intelligence-review/)**Xiaowei Huang, Wenjie Ruan, Wei Huang, et al.*2023 · 199 citations*
3. **[Defending Against Alignment-Breaking Attacks via Robustly Aligned LLM](https://md.research.elamur.ai/free/en/papers/cao-2024-defending-against-alignment-breaking-attacks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bochuan Cao, Yuanpu Cao, Lu Lin, et al.*2024 · 109 citations*
4. **[Defensive Dual Masking for Robust Adversarial Defense](https://md.research.elamur.ai/free/en/papers/yang-2026-defensive-dual-masking-robust-adversarial/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Wangli Yang, Jie Yang, Yi Guo, et al.*2026 · 1 citation*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/zeng-2023-certified-robustness-text-adversarial-attacks/) — Certified Robustness to Text Adversarial Attacks by Randomized [MASK]