---
title: "Who cites Liqun Chen — 105 papers of our library"
description: "105 papers of the Elamur Research library cite the works of Liqun Chen, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/liqun-chen/cited-by/"
---
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# Who cites Liqun Chen

105 citations of their works from 105 papers of our library (of the 149,439 whose bibliographies we read) · 12 with a page here, the most cited first · [← Liqun Chen](https://md.research.elamur.ai/free/en/authors/liqun-chen/)

1. **[Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/min-2021-recent-advances-natural-language-processing/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Bonan Min, Hayley Ross, Elior Sulem, et al.*2021 · 1,556 citations*
2. **[Explainability for Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/zhao-2023-explainability-large-language-models-survey/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Haiyan Zhao, Hanjie Chen, Fan Yang, et al.*2023 · 790 citations*
3. **[From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models](https://md.research.elamur.ai/free/en/papers/feng-2023-pretraining-data-language-models-downstream/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shangbin Feng, Chan Young Park, Yuhan Liu, et al.*2023 · 311 citations*
4. **[Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and Improving Models](https://md.research.elamur.ai/free/en/papers/wu-2021-polyjuice-generating-counterfactuals-explaining-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tongshuang Wu, Marco Tulio Ribeiro, Jeffrey Heer, et al.*2021 · 277 citations*
5. **[Gradient-based Adversarial Attacks against Text Transformers](https://md.research.elamur.ai/free/en/papers/guo-2021-gradient-based-adversarial-attacks-against/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chuan Guo, Alexandre Sablayrolles, Hervé Jégou, et al.*2021 · 189 citations*
6. **[Measure and Improve Robustness in NLP Models: A Survey](https://md.research.elamur.ai/free/en/papers/wang-2022-measure-improve-robustness-nlp-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Xuezhi Wang, Haohan Wang, Diyi Yang*2022 · 148 citations*
7. **[NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation](https://md.research.elamur.ai/free/en/papers/dhole-2023-nl-augmenter-framework-task-sensitive/) [Northern European Journal of Language Technology](https://md.research.elamur.ai/free/en/venues/northern-european-journal-of-language-technology/)**Kaustubh Dhole, Varun Gangal, Sebastian Gehrmann, et al.*2023 · 86 citations*
8. **[Arabic Synonym BERT-based Adversarial Examples for Text Classification](https://md.research.elamur.ai/free/en/papers/alshahrani-2024-arabic-synonym-bert-based-adversarial/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Norah Alshahrani, Saied Alshahrani, Esma Wali, et al.*2024 · 10 citations*
9. **[Persona Jailbreaking in Large Language Models](https://md.research.elamur.ai/free/en/papers/sandhan-2026-persona-jailbreaking-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jivnesh Sandhan, Fei Cheng, Tushar Sandhan, et al.*2026 · 2 citations*
10. **[DAMASHA: Detecting AI in Mixed Adversarial Texts via Segmentation with Human-interpretable Attribution](https://md.research.elamur.ai/free/en/papers/teja-2026-damasha-detecting-ai-mixed-adversarial/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**L. D. M. S. Sai Teja, N. Siva Gopala Krishna, Ufaq Khan, et al.*2026 · 1 citation*
11. **[TinyAttack: Exploring Stylistic Vulnerabilities in Large Language Models](https://md.research.elamur.ai/free/en/papers/mamta-2026-tinyattack-exploring-stylistic-vulnerabilities-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mamta Mamta, Bogdan Grecu, Oana Cocarascu*2026 · 1 citation*
12. **[Robustness Evaluation of ChatGPT Against Chinese Adversarial Attacks (中文对抗攻击下的ChatGPT鲁棒性评估)](https://md.research.elamur.ai/free/en/papers/zhang-2025-robustness-evaluation-chatgpt/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yunting Zhang (张云婷), Lin Ye (叶麟), Baisong Li (李柏松), et al.*2025*

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