Fetching the paper…
Reading the bibliography…
Mainstream backdoor attack methods typically demand substantial tuning data for poisoning, limiting their practicality and potentially degrading the overall performance when applied to Large Language Models (LLMs).
An empirical investigation of catastrophic forgetting in gradient-based neural networks
Ian J Goodfellow, Mehdi Mirza, Da Xiao, Aaron Courville, and Yoshua Bengio · 2013
Earlier work this paper cites.
Recursive deep models for semantic compositionality over a sentiment treebank
Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D Manning, Andrew Y Ng, and Christopher Potts · 2013
Earlier work this paper cites.
Character-level convolutional networks for text classification
Xiang Zhang, Junbo Jake Zhao, and Yann LeCun · 2015
Earlier work this paper cites.
Targeted backdoor attacks on deep learning systems using data poisoning
Xinyun Chen, Chang Liu, Bo Li, Kimberly Lu, and Dawn Song · 2017
Earlier work this paper cites.
Badnets: Identifying vulnerabilities in the machine learning model supply chain
Tianyu Gu, Brendan Dolan-Gavitt, and Siddharth Garg · 2017
Earlier work this paper cites.
Measuring catastrophic forgetting in neural networks
Ronald Kemker, Marc McClure, Angelina Abitino, Tyler Hayes, and Christopher Kanan · 2018
Earlier work this paper cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
Earlier work this paper cites.
Coqa: A conversational question answering challenge
Siva Reddy, Danqi Chen, and Christopher D Manning · 2019
Earlier work this paper cites.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
Earlier work this paper cites.
Can adversarial weight perturbations inject neural backdoors
Siddhant Garg, Adarsh Kumar, Vibhor Goel, and Yingyu Liang · 2020
Earlier work this paper cites.
Transformer feed-forward layers are key-value memories
Mor Geva, Roei Schuster, Jonathan Berant, and Omer Levy · 2020
Earlier work this paper cites.
Weight poisoning attacks on pretrained models
Keita Kurita, Paul Michel, and Graham Neubig · 2020
Earlier work this paper cites.
Badpre: Task-agnostic backdoor attacks to pre-trained nlp foundation models
Kangjie Chen, Yuxian Meng, Xiaofei Sun, Shangwei Guo, Tianwei Zhang, Jiwei Li, and Chun Fan · 2021
Earlier work this paper cites.
Knowledge neurons in pretrained transformers
Damai Dai, Li Dong, Yaru Hao, Zhifang Sui, Baobao Chang, and Furu Wei · 2021
Cited alongside, same era.
Backdoor attacks on pre-trained models by layerwise weight poisoning
Linyang Li, Demin Song, Xiaonan Li, Jiehang Zeng, Ruotian Ma, and Xipeng Qiu · 2021
Cited alongside, same era.
Eric Mitchell, Charles Lin, Antoine Bosselut, Chelsea Finn, and Christopher D Manning · 2021
Cited alongside, same era.
Just how toxic is data poisoning? a unified benchmark for backdoor and data poisoning attacks
Avi Schwarzschild, Micah Goldblum, Arjun Gupta, John P Dickerson, and Tom Goldstein · 2021
Cited alongside, same era.
Bddr: An effective defense against textual backdoor attacks
Kun Shao, Junan Yang, Yang Ai, Hui Liu, and Yu Zhang · 2021
Cited alongside, same era.
Coprotector: Protect open-source code against unauthorized training usage with data poisoning
Zhensu Sun, Xiaoning Du, Fu Song, Mingze Ni, and Li Li · 2022
Later among the works it cites.
Prompt injection attack against llm-integrated applications
Yi Liu, Gelei Deng, Yuekang Li, Kailong Wang, Tianwei Zhang, Yepang Liu, Haoyu Wang, Yan Zheng, and Yang Liu · 2023
Later among the works it cites.
An empirical study of catastrophic forgetting in large language models during continual fine-tuning
Yun Luo, Zhen Yang, Fandong Meng, Yafu Li, Jie Zhou, and Yue Zhang · 2023
Later among the works it cites.
Shiwen Ni, Dingwei Chen, Chengming Li, Xiping Hu, Ruifeng Xu, and Min Yang · 2023
Later among the works it cites.
Can lms learn new entities from descriptions? challenges in propagating injected knowledge
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Neural network surgery: Injecting data patterns into pre-trained models with minimal instance-wise side effects
Zhiyuan Zhang, Xuancheng Ren, Qi Su, Xu Sun, and Bin He · 2021
Cited alongside, same era.
Badprompt: Backdoor attacks on continuous prompts
Xiangrui Cai, Haidong Xu, Sihan Xu, Ying Zhang, et al · 2022
Cited alongside, same era.
Clean-image backdoor: Attacking multi-label models with poisoned labels only
Kangjie Chen, Xiaoxuan Lou, Guowen Xu, Jiwei Li, and Tianwei Zhang · 2022
Cited alongside, same era.
Thomas Hartvigsen, Swami Sankaranarayanan, Hamid Palangi, Yoon Kim, and Marzyeh Ghassemi · 2022
Cited alongside, same era.
Large language models with controllable working memory
Daliang Li, Ankit Singh Rawat, Manzil Zaheer, Xin Wang, Michal Lukasik, Andreas Veit, Felix Yu, and Sanjiv Kumar · 2022
Cited alongside, same era.
Fixing model bugs with natural language patches
Shikhar Murty, Christopher D Manning, Scott Lundberg, and Marco Tulio Ribeiro · 2022
Cited alongside, same era.
Defending against stealthy backdoor attacks
Sangeet Sagar, Abhinav Bhatt, and Abhijith Srinivas Bidaralli · 2022
Cited alongside, same era.
Yasumasa Onoe, Michael JQ Zhang, Shankar Padmanabhan, Greg Durrett, and Eunsol Choi · 2023
Later among the works it cites.
Guilherme Penedo, Quentin Malartic, Daniel Hesslow, Ruxandra Cojocaru, Alessandro Cappelli, Hamza Alobeidli, Baptiste Pannier, Ebtesam Almazrouei, and Julien Launay · 2023
Later among the works it cites.
Badgpt: Exploring security vulnerabilities of chatgpt via backdoor attacks to instructgpt
Jiawen Shi, Yixin Liu, Pan Zhou, and Lichao Sun · 2023
Later among the works it cites.
Stanford alpaca: an instruction-following llama model
Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B Hashimoto · 2023
Later among the works it cites.
Poisoning language models during instruction tuning
Alexander Wan, Eric Wallace, Sheng Shen, and Dan Klein · 2023
Later among the works it cites.
Knowledge editing for large language models: A survey
Song Wang, Yaochen Zhu, Haochen Liu, Zaiyi Zheng, Chen Chen, et al · 2023
Later among the works it cites.
Depn: Detecting and editing privacy neurons in pretrained language models
Xinwei Wu, Junzhuo Li, Minghui Xu, Weilong Dong, Shuangzhi Wu, Chao Bian, and Deyi Xiong · 2023
Later among the works it cites.
Instructions as backdoors: Backdoor vulnerabilities of instruction tuning for large language models
Jiashu Xu, Mingyu Derek Ma, Fei Wang, Chaowei Xiao, and Muhao Chen · 2023
Later among the works it cites.