---
title: "Who cites Yihe Deng — 328 papers of our library"
description: "328 papers of the Elamur Research library cite the works of Yihe Deng, found in their bibliographies; the most cited first."
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---
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# Who cites Yihe Deng

328 citations of their works from 328 papers of our library (of the 149,439 whose bibliographies we read) · 39 with a page here, the most cited first · [← Yihe Deng](https://md.research.elamur.ai/free/en/authors/yihe-deng/)

1. **[The Rise and Potential of Large Language Model Based Agents: A Survey](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Zhiheng Xi, Wenxiang Chen, Xin Guo, et al.*2023 · 1,272 citations*
2. **[TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP](https://md.research.elamur.ai/free/en/papers/morris-2020-textattack-framework-adversarial-attacks-data/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**John X. Morris, Eli Lifland, Jin Yong Yoo, et al.*2020 · 863 citations*
3. **[BERT-ATTACK: Adversarial Attack Against BERT Using BERT](https://md.research.elamur.ai/free/en/papers/li-2020-bert-attack-adversarial-attack-against/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Linyang Li, Ruotian Ma, Qipeng Guo, et al.*2020 · 843 citations*
4. **[BAE: BERT-based Adversarial Examples for Text Classification](https://md.research.elamur.ai/free/en/papers/garg-2020-bae-bert-based-adversarial-examples/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Siddhant Garg, Goutham Ramakrishnan*2020 · 666 citations*
5. [**A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications arXiv:2402.07927**Pranab Sahoo; Ayush Kumar Singh; Sriparna Saha; Vinija Jain; Samrat Mondal;, Aman Chadha*2024 · 375 citations*](https://md.research.elamur.ai/free/en/papers/sahoo-2024-systematic-survey-prompt-engineering-large/)
6. **[Word-level Textual Adversarial Attacking as Combinatorial Optimization](https://md.research.elamur.ai/free/en/papers/zang-2020-word-level-textual-adversarial-attacking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuan Zang, Fanchao Qi, Chenghao Yang, et al.*2020 · 340 citations*
7. **[Contextualized Perturbation for Textual Adversarial Attack](https://md.research.elamur.ai/free/en/papers/li-2021-contextualized-perturbation-textual-adversarial-attack/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Dianqi Li, Yizhe Zhang, Hao Peng, et al.*2021 · 283 citations*
8. **[Large Language Models for Data Annotation and Synthesis: A Survey](https://md.research.elamur.ai/free/en/papers/tan-2024-large-language-models-data-annotation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Tan, Dawei Li, Song Wang, et al.*2024 · 262 citations*
9. **[CLIFF: Contrastive Learning for Improving Faithfulness and Factuality in Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/cao-2021-cliff-contrastive-learning-improving-faithfulness/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shuyang Cao, Lu Wang*2021 · 260 citations*
10. **[An Empirical Survey of Data Augmentation for Limited Data Learning in NLP](https://md.research.elamur.ai/free/en/papers/chen-2023-empirical-survey-data-augmentation-limited/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jiaao Chen, Derek Tam, Colin Raffel, et al.*2023 · 254 citations*
11. **[Supporting Clustering with Contrastive Learning](https://md.research.elamur.ai/free/en/papers/zhang-2021-supporting-clustering-contrastive-learning/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Dejiao Zhang, Feng Nan, Xiaokai Wei, et al.*2021 · 239 citations*
12. **[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*
13. [**The Prompt Report: A Systematic Survey of Prompt Engineering Techniques arXiv:2406.06608**Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.*2024 · 189 citations*](https://md.research.elamur.ai/free/en/papers/schulhoff-2024-prompt-report-systematic-survey-prompt/)
14. **[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*
15. **[Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style Transfer](https://md.research.elamur.ai/free/en/papers/qi-2021-mind-style-text-adversarial-backdoor/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Fanchao Qi, Yangyi Chen, Xurui Zhang, et al.*2021 · 189 citations*
16. [**SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks arXiv:2310.03684**Alexander Robey, Eric Wong, Hamed Hassani, et al.*2023 · 164 citations*](https://md.research.elamur.ai/free/en/papers/robey-2023-smoothllm-defending-large-language-models/)
17. **[Explaining NLP Models via Minimal Contrastive Editing (MiCE)](https://md.research.elamur.ai/free/en/papers/ross-2021-explaining-nlp-models-minimal-contrastive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Alexis Ross, Ana Marasović, Matthew Peters*2021 · 155 citations*
18. **[Reevaluating Adversarial Examples in Natural Language](https://md.research.elamur.ai/free/en/papers/morris-2020-reevaluating-adversarial-examples-natural-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**John Morris, Eli Lifland, Jack Lanchantin, et al.*2020 · 151 citations*
19. **[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*
20. **[Towards Robustness of Text-to-SQL Models against Synonym Substitution](https://md.research.elamur.ai/free/en/papers/gan-2021-robustness-text-sql-models-against/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yujian Gan, Xinyun Chen, Qiuping Huang, et al.*2021 · 143 citations*
21. **[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*
22. **[Certified Robustness to Text Adversarial Attacks by Randomized MASK](https://md.research.elamur.ai/free/en/papers/zeng-2023-certified-robustness-text-adversarial-attacks/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Jiehang Zeng, Jianhan Xu, Xiaoqing Zheng, et al.*2023 · 101 citations*
23. [**Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning arXiv:2309.05444**Ted Zadouri, Ahmet Ustun, Arash Ahmadian, et al.*2023 · 69 citations*](https://md.research.elamur.ai/free/en/papers/zadouri-2023-pushing-mixture-experts-limit-extremely/)
24. [**Tokenization counts: the impact of tokenization on arithmetic in frontier LLMs arXiv:2402.14903**Aaditya K. Singh, DJ Strouse*2024 · 55 citations*](https://md.research.elamur.ai/free/en/papers/singh-2024-tokenization-counts-impact-tokenization-arithmetic/)
25. [**Explore, Establish, Exploit: Red Teaming Language Models from Scratch arXiv:2306.09442**Stephen Casper, Jason Lin, Joe Kwon, et al.*2023 · 52 citations*](https://md.research.elamur.ai/free/en/papers/casper-2023-explore-establish-exploit-red-teaming/)
26. **[Interactive Evolution: A Neural-Symbolic Self-Training Framework For Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2025-interactive-evolution-neural-symbolic-self/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fangzhi Xu, Qiushi Sun, Kanzhi Cheng, et al.*2025 · 15 citations*
27. **[Mix-of-Granularity: Optimize the Chunking Granularity for Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/zhong-2025-mix-granularity-optimize-chunking-granularity/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Zijie Zhong, Hanwen Liu, Xiaoya Cui, et al.*2025 · 13 citations*
28. [**The Trickle-down Impact of Reward (In-)consistency on RLHF arXiv:2309.16155**Lingfeng Shen, Sihao Chen, Linfeng Song, et al.*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-trickle-down-impact-reward-consistency/)
29. **[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*
30. [**A Closer Look into the Robustness of Neural Dependency Parsers Using Better Adversarial Examples**Yuxuan Wang, Wanxiang Che, Ivan Titov, et al.*2021 · 8 citations*](https://md.research.elamur.ai/free/en/papers/wang-2021-closer-look-into-robustness-neural/)
31. **[Aligning Large Language Models via Fully Self-Synthetic Data](https://md.research.elamur.ai/free/en/papers/yin-2026-aligning-large-language-models-fully/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shangjian Yin, Zhepei Wei, Xinyu Zhu, et al.*2026 · 2 citations*
32. **[Exploring Generative Process Reward Modeling for Semi-Structured Data: A Case Study of Table Question Answering](https://md.research.elamur.ai/free/en/papers/tang-2026-exploring-generative-process-reward-modeling/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Lei Tang, Wei Zhou, Mohsen Mesgar*2026 · 2 citations*
33. **[One Refiner to Unlock Them All: Inference-Time Reasoning Elicitation via Reinforcement Query Refinement](https://md.research.elamur.ai/free/en/papers/zhou-2026-one-refiner-unlock-them-all/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixiao Zhou, Dongzhou Cheng, Zhiliang wu, et al.*2026 · 2 citations*
34. **[FLUKE: A Linguistically-Driven and Task-Agnostic Framework for Robustness Evaluation](https://md.research.elamur.ai/free/en/papers/otmakhova-2026-fluke-linguistically-driven-task-agnostic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yulia Otmakhova, Thinh Hung Truong, Rahmad Mahendra, et al.*2026 · 1 citation*
35. **[Are Emotion and Rhetoric Neurons in LLM? Neuron Recognition and Adaptive Masking for Emotion-Rhetoric Prediction Steering](https://md.research.elamur.ai/free/en/papers/zheng-2026-are-emotion-rhetoric-neurons-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Li Zheng, Xin Zhang, Shuyi He, et al.*2026*
36. **[Breaking the Generator Barrier: Disentangled Representation for Generalizable AI-Text Detection](https://md.research.elamur.ai/free/en/papers/pu-2026-breaking-generator-barrier-disentangled-representation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiao Pu, Zepeng Cheng, Lin Yuan, et al.*2026*
37. **[Gradient-Guided Multi-Judge Prompt Optimization](https://md.research.elamur.ai/free/en/papers/zhao-2026-gradient-guided-multi-judge-prompt/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**ChenZhuo Zhao, Xinda Wang, Pu Zhao, et al.*2026*
38. **[SPARTA: Evaluating Reasoning Segmentation Robustness through Black-Box Adversarial Paraphrasing in Text Autoencoder Latent Space](https://md.research.elamur.ai/free/en/papers/zinkovich-2026-sparta-evaluating-reasoning-segmentation-robustness/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Viktoriia Zinkovich, Anton Antonov, Andrei Spiridonov, et al.*2026*
39. **[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*

289 more citing papers of our library have no page here yet.

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