--- title: "Who cites BadNets: Identifying — 101 citing papers" description: "101 papers of the Elamur Research library cite «BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain», found in their…" canonical: "https://research.elamur.ai/free/en/papers/gu-2017-badnets-identifying-vulnerabilities-machine-learning/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/gu-2017-badnets-identifying-vulnerabilities-machine-learning/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [BadNets: Identifying Vulnerabilities in the…](https://md.research.elamur.ai/free/en/papers/gu-2017-badnets-identifying-vulnerabilities-machine-learning/) / cited by # Who cites «BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain» 101 papers of our library cite it (of the 149,439 whose bibliographies we read) · 15 with a page here, the most cited first · [← back to «BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain»](https://md.research.elamur.ai/free/en/papers/gu-2017-badnets-identifying-vulnerabilities-machine-learning/) 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. [**Unleashing the potential of prompt engineering for large language models arXiv:2310.14735 · Patterns 6(6) 101,260 (2025)**Banghao Chen, Zhaofeng Zhang, Nicolas Langrene, et al.*2023 · 536 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-unleashing-potential-prompt-engineering-large/) 3. **[Weight Poisoning Attacks on Pretrained Models](https://md.research.elamur.ai/free/en/papers/kurita-2020-weight-poisoning-attacks-pretrained-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Keita Kurita, Paul Michel, Graham Neubig*2020 · 416 citations* 4. [**Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! arXiv:2310.03693**Xiangyu Qi, Yi Zeng, Tinghao Xie, et al.*2023 · 355 citations*](https://md.research.elamur.ai/free/en/papers/qi-2023-fine-tuning-aligned-language-models/) 5. **[ONION: A Simple and Effective Defense Against Textual Backdoor Attacks](https://md.research.elamur.ai/free/en/papers/qi-2021-onion-simple-effective-defense-against/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Fanchao Qi, Yangyi Chen, Mukai Li, et al.*2021 · 280 citations* 6. [**The Curse of Recursion: Training on Generated Data Makes Models Forget arXiv:2305.17493**Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao, et al.*2023 · 255 citations*](https://md.research.elamur.ai/free/en/papers/shumailov-2023-curse-recursion-training-generated-data/) 7. **[Hidden Killer: Invisible Textual Backdoor Attacks with Syntactic Trigger](https://md.research.elamur.ai/free/en/papers/qi-2021-hidden-killer-invisible-textual-backdoor/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fanchao Qi, Mukai Li, Yangyi Chen, et al.*2021 · 238 citations* 8. **[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* 9. **[Be Careful about Poisoned Word Embeddings: Exploring the Vulnerability of the Embedding Layers in NLP Models](https://md.research.elamur.ai/free/en/papers/yang-2021-be-careful-about-poisoned-word/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Wenkai Yang, Lei Li, Zhiyuan Zhang, et al.*2021 · 135 citations* 10. **[RAP: Robustness-Aware Perturbations for Defending against Backdoor Attacks on NLP Models](https://md.research.elamur.ai/free/en/papers/yang-2021-rap-robustness-aware-perturbations-defending/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wenkai Yang, Yankai Lin, Peng Li, et al.*2021 · 112 citations* 11. [**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/) 12. **[Backdoors in RLVR: Jailbreak Backdoors in LLMs From Verifiable Reward](https://md.research.elamur.ai/free/en/papers/guo-2026-backdoors-rlvr-jailbreak-backdoors-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weiyang Guo, Zesheng Shi, Zeen Zhu, et al.*2026 · 10 citations* 13. **[P2P: A Poison-to-Poison Remedy for Reliable Backdoor Defense in LLMs](https://md.research.elamur.ai/free/en/papers/zhao-2026-p2p-poison-poison-remedy-reliable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shuai Zhao, Xinyi Wu, Shiqian Zhao, et al.*2026 · 3 citations* 14. **[Compiling Activation Steering into Weights via Null-Space Constraints for Stealthy Backdoors](https://md.research.elamur.ai/free/en/papers/yin-2026-compiling-activation-steering-into-weights/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rui Yin, Tianxu Han, Naen Xu, et al.*2026 · 1 citation* 15. **[Why LoRA Fails to Forget: Regularized Low-Rank Adaptation Against Backdoors in Language Models](https://md.research.elamur.ai/free/en/papers/luong-2026-why-lora-fails-forget-regularized/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hoang-Chau Luong, Lingwei Chen*2026* 86 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/gu-2017-badnets-identifying-vulnerabilities-machine-learning/) — BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain