---
title: "Who cites Measure and Improve — 64 citing papers"
description: "64 papers of the Elamur Research library cite «Measure and Improve Robustness in NLP Models: A Survey», found in their bibliographies…"
canonical: "https://research.elamur.ai/free/en/papers/wang-2022-measure-improve-robustness-nlp-models/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/wang-2022-measure-improve-robustness-nlp-models/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Measure and Improve Robustness in NLP Models: A…](https://md.research.elamur.ai/free/en/papers/wang-2022-measure-improve-robustness-nlp-models/) / cited by

# Who cites «Measure and Improve Robustness in NLP Models: A Survey»

64 papers of our library cite it (of the 141,840 whose bibliographies we read) · 3 with a page here, the most cited first · [← back to «Measure and Improve Robustness in NLP Models: A Survey»](https://md.research.elamur.ai/free/en/papers/wang-2022-measure-improve-robustness-nlp-models/)

1. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 226 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
2. [**Evaluation of Adversarial Robustness in Arabic Language Models arXiv:2607.25814**Anwar Alajmi, Ayed Salman, Imtiaz Ahmad*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/alajmi-2026-evaluation-adversarial-robustness-arabic-language/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/wang-2022-measure-improve-robustness-nlp-models/) — Measure and Improve Robustness in NLP Models: A Survey