🧑‍🔬 Who cites Daniel Lowd

400 citations of their works from 375 papers of our library (of the 141,840 whose bibliographies we read) · 47 with a page here, the most cited first · ← Daniel Lowd

1. How Can We Know What Language Models Know?Transactions of the Association for Computational Linguistics (TACL)Zhengbao Jiang, Frank F. Xu, Jun Araki, et al.2020 · 1,501 citations
2. Generating Natural Language Adversarial ExamplesConference on Empirical Methods in Natural Language Processing (EMNLP)Moustafa Alzantot, Yash Sharma, Ahmed Elgohary, et al.2018 · 1,104 citations
3. Universal and Transferable Adversarial Attacks on Aligned Language ModelsarXiv:2307.15043Andy Zou, Zifan Wang, Nicholas Carlini, et al.2023 · 951 citations
4. Generating Natural Language Adversarial Examples through Probability Weighted Word SaliencyAnnual Meeting of the Association for Computational Linguistics (ACL)Shuhuai Ren, Yihe Deng, Kun He, et al.2019 · 884 citations
5. TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLPConference on Empirical Methods in Natural Language Processing (EMNLP)John X. Morris, Eli Lifland, Jin Yong Yoo, et al.2020 · 858 citations
6. Analysis Methods in Neural Language Processing: A SurveyTransactions of the Association for Computational Linguistics (TACL)Yonatan Belinkov, James Glass2019 · 737 citations
7. Red Teaming Language Models with Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Ethan Perez, Saffron Huang, Francis Song, et al.2022 · 666 citations
8. BAE: BERT-based Adversarial Examples for Text ClassificationConference on Empirical Methods in Natural Language Processing (EMNLP)Siddhant Garg, Goutham Ramakrishnan2020 · 665 citations
9. Plug and Play Language Models: A Simple Approach to Controlled Text GenerationarXiv:1912.02164Sumanth Dathathri, Andrea Madotto, Janice Lan, et al.2019 · 567 citations
10. FreeLB: Enhanced Adversarial Training for Natural Language UnderstandingarXiv:1909.11764Chen Zhu, Yu Cheng, Zhe Gan, et al.2019 · 446 citations
11. Weight Poisoning Attacks on Pretrained ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Keita Kurita, Paul Michel, Graham Neubig2020 · 415 citations
12. Combating Adversarial Misspellings with Robust Word RecognitionAnnual Meeting of the Association for Computational Linguistics (ACL)Danish Pruthi, Bhuwan Dhingra, Zachary C. Lipton2019 · 389 citations
13. Word-level Textual Adversarial Attacking as Combinatorial OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Yuan Zang, Fanchao Qi, Chenghao Yang, et al.2020 · 340 citations
14. Certified Robustness to Adversarial Word SubstitutionsConference on Empirical Methods in Natural Language Processing (EMNLP)Robin Jia, Aditi Raghunathan, Kerem Göksel, et al.2019 · 337 citations
15. Robust Neural Machine Translation with Doubly Adversarial InputsAnnual Meeting of the Association for Computational Linguistics (ACL)Yong Cheng, Lu Jiang, Wolfgang Macherey2019 · 324 citations
16. HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust RefusalarXiv:2402.04249Mantas Mazeika, Long Phan, Xuwang Yin, et al.2024 · 312 citations
17. Scaling Laws for Reward Model OveroptimizationarXiv:2210.10760Leo Gao, John Schulman, Jacob Hilton2022 · 302 citations
18. Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human AttackConference on Empirical Methods in Natural Language Processing (EMNLP)Emily Dinan, Samuel Humeau, Bharath Chintagunta, et al.2019 · 292 citations
19. Contextualized Perturbation for Textual Adversarial AttackConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Dianqi Li, Yizhe Zhang, Hao Peng, et al.2021 · 282 citations
20. An Empirical Survey of Data Augmentation for Limited Data Learning in NLPTransactions of the Association for Computational Linguistics (TACL)Jiaao Chen, Derek Tam, Colin Raffel, et al.2023 · 253 citations
21. Tree of Attacks: Jailbreaking Black-Box LLMs AutomaticallyConference on Neural Information Processing Systems (NeurIPS)Anay Mehrotra, Manolis Zampetakis, Paul Kassianik, et al.2023 · 245 citations
22. Baseline Defenses for Adversarial Attacks Against Aligned Language ModelsarXiv:2309.00614Neel Jain, Avi Schwarzschild, Yuxin Wen, et al.2023 · 225 citations
23. On Adversarial Examples for Character-Level Neural Machine TranslationInternational Conference on Computational Linguistics (COLING)Javid Ebrahimi, Daniel Lowd, Dejing Dou2018 · 223 citations
24. LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation MethodsarXiv:2412.05579Haitao Li, Qian Dong, Junjie Chen, et al.2024 · 189 citations
25. Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style TransferConference on Empirical Methods in Natural Language Processing (EMNLP)Fanchao Qi, Yangyi Chen, Xurui Zhang, et al.2021 · 188 citations
26. Gradient-based Adversarial Attacks against Text TransformersConference on Empirical Methods in Natural Language Processing (EMNLP)Chuan Guo, Alexandre Sablayrolles, Hervé Jégou, et al.2021 · 187 citations
27. Explaining Black Box Predictions and Unveiling Data Artifacts through Influence FunctionsAnnual Meeting of the Association for Computational Linguistics (ACL)Xiaochuang Han, Byron C. Wallace, Yulia Tsvetkov2020 · 181 citations
28. AllenNLP Interpret: A Framework for Explaining Predictions of NLP ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Eric Wallace, Jens Tuyls, Junlin Wang, et al.2019 · 180 citations
29. Achieving Verified Robustness to Symbol Substitutions via Interval Bound PropagationConference on Empirical Methods in Natural Language Processing (EMNLP)Po-Sen Huang, Robert Stanforth, Johannes Welbl, et al.2019 · 163 citations
30. On Evaluation of Adversarial Perturbations for Sequence-to-Sequence ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Paul Michel, Xian Li, Graham Neubig, et al.2019 · 162 citations
31. Training on Synthetic Noise Improves Robustness to Natural Noise in Machine TranslationWorkshop on Noisy User-generated TextVladimir Karpukhin, Omer Levy, Jacob Eisenstein, et al.2019 · 159 citations
32. Explaining NLP Models via Minimal Contrastive Editing (MiCE)Findings of the Association for Computational LinguisticsAlexis Ross, Ana Marasović, Matthew Peters2021 · 154 citations
33. Reevaluating Adversarial Examples in Natural LanguageFindings of the Association for Computational LinguisticsJohn Morris, Eli Lifland, Jack Lanchantin, et al.2020 · 151 citations
34. Measure and Improve Robustness in NLP Models: A SurveyConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Xuezhi Wang, Haohan Wang, Diyi Yang2022 · 148 citations
35. Text Processing Like Humans Do: Visually Attacking and Shielding NLP SystemsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Steffen Eger, Gözde Gül Şahin, Andreas Rücklé, et al.2019 · 147 citations
36. Towards Robustness of Text-to-SQL Models against Synonym SubstitutionAnnual Meeting of the Association for Computational Linguistics (ACL)Yujian Gan, Xinyun Chen, Qiuping Huang, et al.2021 · 143 citations
37. Inoculation by Fine-Tuning: A Method for Analyzing Challenge DatasetsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Nelson F. Liu, Roy Schwartz, Noah A. Smith2019 · 137 citations
38. It's Morphin' Time! Combating Linguistic Discrimination with Inflectional PerturbationsAnnual Meeting of the Association for Computational Linguistics (ACL)Samson Tan, Shafiq Joty, Min-Yen Kan, et al.2020 · 130 citations
39. Don't Take the Premise for Granted: Mitigating Artifacts in Natural Language InferenceAnnual Meeting of the Association for Computational Linguistics (ACL)Yonatan Belinkov, Adam Poliak, Stuart Shieber, et al.2019 · 121 citations
40. Defending Against Alignment-Breaking Attacks via Robustly Aligned LLMAnnual Meeting of the Association for Computational Linguistics (ACL)Bochuan Cao, Yuanpu Cao, Lu Lin, et al.2024 · 107 citations
41. Survey of Vulnerabilities in Large Language Models Revealed by Adversarial AttacksarXiv:2310.10844Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.2023 · 83 citations
42. Avoiding the Hypothesis-Only Bias in Natural Language Inference via Ensemble Adversarial TrainingConference on Empirical Methods in Natural Language Processing (EMNLP)Joe Stacey, Pasquale Minervini, Haim Dubossarsky, et al.2020 · 67 citations
43. VALUE: Understanding Dialect Disparity in NLUCaleb Ziems, Jiaao Chen, Camille Harris, et al.2022 · 65 citations
44. Evaluating and Enhancing the Robustness of Neural Network-based Dependency Parsing Models with Adversarial ExamplesXiaoqing Zheng, Jiehang Zeng, Yi Zhou, et al.2020 · 54 citations
45. Diff4TST: Masked Diffusion Language Model for Text Style TransferAnnual Meeting of the Association for Computational Linguistics (ACL)Xinchen Ma, Gaole He, Yunshi Lan, et al.2026
46. SPARTA: Evaluating Reasoning Segmentation Robustness through Black-Box Adversarial Paraphrasing in Text Autoencoder Latent SpaceConference of the European Chapter of the Association for Computational Linguistics (EACL)Viktoriia Zinkovich, Anton Antonov, Andrei Spiridonov, et al.2026
47. Robustness Evaluation of ChatGPT Against Chinese Adversarial Attacks (中文对抗攻击下的ChatGPT鲁棒性评估)Journal of SoftwareYunting Zhang (张云婷), Lin Ye (叶麟), Baisong Li (李柏松), et al.2025

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

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/authors/daniel-lowd/cited-by/