Fetching the paper…
Reading the bibliography…
LLMs are often used by downstream users as teacher models for knowledge distillation, compressing their capabilities into memory-efficient models.
A backdoor attack against lstm-based text classification systems, 2019
Jiazhu Dai and Chuanshuai Chen · 1905
Earlier work this paper cites.
Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter, 2020
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf · 1910
Earlier work this paper cites.
Weight poisoning attacks on pre-trained models, 2020
Keita Kurita, Paul Michel, and Graham Neubig · 2004
Earlier work this paper cites.
Measuring massive multitask language understanding, 2021
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt · 2009
Earlier work this paper cites.
Distilling the knowledge in a neural network, 2015
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
Earlier work this paper cites.
Targeted backdoor attacks on deep learning systems using data poisoning, 2017
Xinyun Chen, Chang Liu, Bo Li, Kimberly Lu, and Dawn Song · 2017
Earlier work this paper cites.
Think you have solved question answering? try arc, the ai2 reasoning challenge, 2018
Peter Clark, Isaac Cowhey, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Carissa Schoenick, and Oyvind Tafjord · 2018
Earlier work this paper cites.
Badnets: Identifying vulnerabilities in the machine learning model supply chain, 2019
Tianyu Gu, Brendan Dolan-Gavitt, and Siddharth Garg · 2019
Earlier work this paper cites.
Badnl: Backdoor attacks against nlp models with semantic-preserving improvements
Xiaoyi Chen, Ahmed Salem, Dingfan Chen, Michael Backes, Shiqing Ma, Qingni Shen, Zhonghai Wu, and Yang Zhang · 2021
Earlier work this paper cites.
Anti-distillation backdoor attacks: Backdoors can really survive in knowledge distillation
Yunjie Ge, Qian Wang, Baolin Zheng, Xinlu Zhuang, Qi Li, Chao Shen, and Cong Wang · 2021
Earlier work this paper cites.
Hidden killer: Invisible textual backdoor attacks with syntactic trigger, 2021
Fanchao Qi, Mukai Li, Yangyi Chen, Zhengyan Zhang, Zhiyuan Liu, Yasheng Wang, and Maosong Sun · 2021
Earlier work this paper cites.
Rethinking stealthiness of backdoor attack against NLP models
Wenkai Yang, Yankai Lin, Peng Li, Jie Zhou, and Xu Sun · 2021
Earlier work this paper cites.
Truthfulqa: Measuring how models mimic human falsehoods, 2022
Stephanie Lin, Jacob Hilton, and Owain Evans · 2022
Earlier work this paper cites.
Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
Earlier work this paper cites.
Exploring the universal vulnerability of prompt-based learning paradigm, 2022
Lei Xu, Yangyi Chen, Ganqu Cui, Hongcheng Gao, and Zhiyuan Liu · 2022
Earlier work this paper cites.
Code alpaca: An instruction-following llama model for code generation
Sahil Chaudhary · 2023
Earlier work this paper cites.
Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality, March 2023
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing · 2023
Cited alongside, same era.
Free dolly: Introducing the world’s first truly open instruction-tuned llm, 2023
Mike Conover, Matt Hayes, Ankit Mathur, Jianwei Xie, Jun Wan, Sam Shah, Ali Ghodsi, Patrick Wendell, Matei Zaharia, and Reynold Xin · 2023
Cited alongside, same era.
Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de Las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al · 2023
Cited alongside, same era.
Multi-target backdoor attacks for code pre-trained models, 2023
Yanzhou Li, Shangqing Liu, Kangjie Chen, Xiaofei Xie, Tianwei Zhang, and Yang Liu · 2023
Cited alongside, same era.
The flan collection: Designing data and methods for effective instruction tuning, 2023
Sleeper agents: Training deceptive llms that persist through safety training, 2024
Evan Hubinger, Carson Denison, Jesse Mu, Mike Lambert, Meg Tong, Monte MacDiarmid, Tamera Lanham, Daniel M. Ziegler, Tim Maxwell, Newton Cheng, Adam Jermyn, Amanda Askell, Ansh Radhakrishnan, Cem Anil, David Duvenaud, Deep Ganguli, Fazl Barez, Jack Clark, Kamal Ndousse, Kshitij Sachan, Michael Sellitto, Mrinank Sharma, Nova DasSarma, Roger Grosse, Shauna Kravec, Yuntao Bai, Zachary Witten, Marina Favaro, Jan Brauner, Holden Karnofsky, Paul Christiano, Samuel R. Bowman, Logan Graham, Jared Kaplan, Sören Mindermann, Ryan Greenblatt, Buck Shlegeris, Nicholas Schiefer, and Ethan Perez · 2024
Later among the works it cites.
Shortcuts everywhere and nowhere: Exploring multi-trigger backdoor attacks, 2024
Yige Li, Jiabo He, Hanxun Huang, Jun Sun, Xingjun Ma, and Yu-Gang Jiang · 2024
Later among the works it cites.
Ink: Inheritable natural backdoor attack against model distillation, 2024
Xiaolei Liu, Ming Yi, Kangyi Ding, Bangzhou Xin, Yixiao Xu, Li Yan, and Chao Shen · 2024
Later among the works it cites.
Universal jailbreak backdoors from poisoned human feedback, 2024
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Shayne Longpre, Le Hou, Tu Vu, Albert Webson, Hyung Won Chung, Yi Tay, Denny Zhou, Quoc V. Le, Barret Zoph, Jason Wei, and Adam Roberts · 2023
Cited alongside, same era.
Orca 2: Teaching small language models how to reason, 2023
Arindam Mitra, Luciano Del Corro, Shweti Mahajan, Andres Codas, Clarisse Simoes, Sahaj Agarwal, Xuxi Chen, Anastasia Razdaibiedina, Erik Jones, Kriti Aggarwal, Hamid Palangi, Guoqing Zheng, Corby Rosset, Hamed Khanpour, and Ahmed Awadallah · 2023
Cited alongside, same era.
Fine-tuning aligned language models compromises safety, even when users do not intend to!, 2023
Xiangyu Qi, Yi Zeng, Tinghao Xie, Pin-Yu Chen, Ruoxi Jia, Prateek Mittal, and Peter Henderson · 2023
Cited alongside, same era.
On the exploitability of instruction tuning, 2023
Manli Shu, Jiongxiao Wang, Chen Zhu, Jonas Geiping, Chaowei Xiao, and Tom Goldstein · 2023
Cited alongside, same era.
Stanford Alpaca: an instruction-following LLaMA model, 2023
Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B. Hashimoto · 2023
Cited alongside, same era.
Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, Dan Bikel, Lukas Blecher, Cristian Canton-Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller, Cynthia Gao, Vedanuj Goswami, Naman Goyal, Anthony Hartshorn, Saghar Hosseini, Rui Hou, Hakan Inan, Marcin Kardas, Viktor Kerkez, Madian Khabsa, Isabel Kloumann, Artem Korenev, Punit Singh Koura, Marie-Anne Lachaux, Thibaut Lavril, Jenya Lee, Diana Liskovich, Yinghai Lu, Yuning Mao, Xavier Martinet, Todor Mihaylov, Pushkar Mishra, Igor Molybog, Yixin Nie, Andrew Poulton, Jeremy Reizenstein, Rashi Rungta, Kalyan Saladi, Alan Schelten, Ruan Silva, Eric Michael Smith, Ranjan Subramanian, Xiaoqing Ellen Tan, Binh Tang, Ross Taylor, Adina Williams, Jian Xiang Kuan, Puxin Xu, Zheng Yan, Iliyan Zarov, Yuchen Zhang, Angela Fan, Melanie Kambadur, Sharan Narang, Aurélien Rodriguez, Robert Stojnic, Sergey Edunov, and Thomas Scialom · 2023
Cited alongside, same era.
Poisoning language models during instruction tuning, 2023
Alexander Wan, Eric Wallace, Sheng Shen, and Dan Klein · 2023
Cited alongside, same era.
Universal and transferable adversarial attacks on aligned language models, 2023
Andy Zou, Zifan Wang, Nicholas Carlini, Milad Nasr, J. Zico Kolter, and Matt Fredrikson · 2023
Cited alongside, same era.
Javier Rando and Florian Tramèr · 2024
Later among the works it cites.
Openmathinstruct-2: Accelerating ai for math with massive open-source instruction data, 2024
Shubham Toshniwal, Wei Du, Ivan Moshkov, Branislav Kisacanin, Alexan Ayrapetyan, and Igor Gitman · 2024
Later among the works it cites.
Backdooring instruction-tuned large language models with virtual prompt injection, 2024
Jun Yan, Vikas Yadav, Shiyang Li, Lichang Chen, Zheng Tang, Hai Wang, Vijay Srinivasan, Xiang Ren, and Hongxia Jin · 2024
Later among the works it cites.
An Yang, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chengyuan Li, Dayiheng Liu, Fei Huang, Haoran Wei, et al · 2024
Later among the works it cites.
Wildchat: 1m chatgpt interaction logs in the wild, 2024
Wenting Zhao, Xiang Ren, Jack Hessel, Claire Cardie, Yejin Choi, and Yuntian Deng · 2024
Later among the works it cites.
Cascading adversarial bias from injection to distillation in language models, 2025
Harsh Chaudhari, Jamie Hayes, Matthew Jagielski, Ilia Shumailov, Milad Nasr, and Alina Oprea · 2025
Closest in time.
Subliminal learning: Language models transmit behavioral traits via hidden signals in data, 2025
Alex Cloud, Minh Le, James Chua, Jan Betley, Anna Sztyber-Betley, Jacob Hilton, Samuel Marks, and Owain Evans · 2025
Closest in time.
Hugging Face
Hugging Face · 2025
Closest in time.
Yige Li, Hanxun Huang, Yunhan Zhao, Xingjun Ma, and Jun Sun · 2025
Closest in time.
Sharegpt
ShareGPT · 2025
Closest in time.
Latent adversarial training improves robustness to persistent harmful behaviors in llms, 2025
Abhay Sheshadri, Aidan Ewart, Phillip Guo, Aengus Lynch, Cindy Wu, Vivek Hebbar, Henry Sleight, Asa Cooper Stickland, Ethan Perez, Dylan Hadfield-Menell, and Stephen Casper · 2025
Closest in time.
Multi-trigger poisoning amplifies backdoor vulnerabilities in llms, 2025
Sanhanat Sivapiromrat, Caiqi Zhang, Marco Basaldella, and Nigel Collier · 2025
Closest in time.