Fetching the paper…
Reading the bibliography…
Retrieval-Augmented Generation (RAG) expands the knowledge boundary of large language models (LLMs) by integrating external knowledge bases, whose construction is often time-consuming and laborious.
Harry potter and the sorcerer’s stone, 2002
Stephen Brown · 2002
Earlier work this paper cites.
The enron corpus: A new dataset for email classification research
Bryan Klimt and Yiming Yang · 2004
Earlier work this paper cites.
Eed: Extended edit distance measure for machine translation
Peter Stanchev, Weiyue Wang, and Hermann Ney · 2019
Earlier work this paper cites.
Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, et al · 2020
Earlier work this paper cites.
Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oğuz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen Tau Yih · 2020
Earlier work this paper cites.
Retrieval augmentation reduces hallucination in conversation
Kurt Shuster, Spencer Poff, Moya Chen, Douwe Kiela, and Jason Weston · 2021
Earlier work this paper cites.
Autolaw: augmented legal reasoning through legal precedent prediction
Robert Zev Mahari · 2021
Earlier work this paper cites.
Extracting training data from large language models
Nicholas Carlini, Florian Tramer, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song, Ulfar Erlingsson, et al · 2021
Earlier work this paper cites.
Improving language models by retrieving from trillions of tokens
Sebastian Borgeaud, Arthur Mensch, Jordan Hoffmann, Trevor Cai, Eliza Rutherford, Katie Millican, George Bm Van Den Driessche, Jean-Baptiste Lespiau, Bogdan Damoc, Aidan Clark, et al · 2022
Earlier work this paper cites.
Lamda: Language models for dialog applications
Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, et al · 2022
Earlier work this paper cites.
Ignore previous prompt: Attack techniques for language models
Fábio Perez and Ian Ribeiro · 2022
Earlier work this paper cites.
Are large pre-trained language models leaking your personal information?
Jie Huang, Hanyin Shao, and Kevin Chen Chuan Chang · 2022
Earlier work this paper cites.
Text revealer: Private text reconstruction via model inversion attacks against transformers
Ruisi Zhang, Seira Hidano, and Farinaz Koushanfar · 2022
Earlier work this paper cites.
Canary extraction in natural language understanding models
Rahil Parikh, Christophe Dupuy, and Rahul Gupta · 2022
Earlier work this paper cites.
Survey of hallucination in natural language generation
Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Ye Jin Bang, Andrea Madotto, and Pascale Fung · 2023
Earlier work this paper cites.
In-context retrieval-augmented language models
Ori Ram, Yoav Levine, Itay Dalmedigos, Dor Muhlgay, Amnon Shashua, Kevin Leyton-Brown, and Yoav Shoham · 2023
Earlier work this paper cites.
Transforming healthcare education: Harnessing large language models for frontline health worker capacity building using retrieval-augmented generation
Yasmina Al Ghadban, Huiqi Yvonne Lu, Uday Adavi, Ankita Sharma, Sridevi Gara, Neelanjana Das, Bhaskar Kumar, Renu John, Praveen Devarsetty, and Jane E Hirst · 2023
Earlier work this paper cites.
Making llms worth every penny: Resource-limited text classification in banking
Lefteris Loukas, Ilias Stogiannidis, Odysseas Diamantopoulos, Prodromos Malakasiotis, and Stavros Vassos · 2023
Earlier work this paper cites.
Mycrunchgpt: A llm assisted framework for scientific machine learning
Varun Kumar, Leonard Gleyzer, Adar Kahana, Khemraj Shukla, and George Em Karniadakis · 2023
Earlier work this paper cites.
An interdisciplinary outlook on large language models for scientific research
James Boyko, Joseph Cohen, Nathan Fox, Maria Han Veiga, Jennifer I Li, Jing Liu, Bernardo Modenesi, Andreas H Rauch, Kenneth N Reid, Soumi Tribedi, et al · 2023
Earlier work this paper cites.
Owasp top 10 for llm applications, access in 2023
OWASP · 2023
Earlier work this paper cites.
Delimiters won’t save you from prompt injection, 2024
Simon Willison · 2023
Earlier work this paper cites.
The rise and potential of large language model based agents: A survey
Zhiheng Xi, Wenxiang Chen, Xin Guo, Wei He, Yiwen Ding, Boyang Hong, Ming Zhang, Junzhe Wang, Senjie Jin, Enyu Zhou, et al · 2023
Earlier work this paper cites.
A multitask, multilingual, multimodal evaluation of chatgpt on reasoning, hallucination, and interactivity
Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, Wenliang Dai, Dan Su, Bryan Wilie, Holy Lovenia, Ziwei Ji, Tiezheng Yu, Willy Chung, et al · 2023
Earlier work this paper cites.
Modelscope-agent: Building your customizable agent system with open-source large language models
Chenliang Li, He Chen, Ming Yan, Weizhou Shen, Haiyang Xu, Zhikai Wu, Zhicheng Zhang, Wenmeng Zhou, Yingda Chen, Chen Cheng, et al · 2023
Earlier work this paper cites.
Autogpt, 2023
Significant Gravitas · 2023
Earlier work this paper cites.
Tree of attacks: Jailbreaking black-box llms automatically
Anay Mehrotra, Manolis Zampetakis, Paul Kassianik, Blaine Nelson, Hyrum Anderson, Yaron Singer, and Amin Karbasi · 2023
Earlier work this paper cites.
Multi-step jailbreaking privacy attacks on chatgpt
Haoran Li, Dadi Guo, Wei Fan, Mingshi Xu, Jie Huang, Fanpu Meng, and Yangqiu Song · 2023
Earlier work this paper cites.
Ethicist: Targeted training data extraction through loss smoothed soft prompting and calibrated confidence estimation
Zhexin Zhang, Jiaxin Wen, and Minlie Huang · 2023
Cited alongside, same era.
Analyzing leakage of personally identifiable information in language models
Nils Lukas, Ahmed Salem, Robert Sim, Shruti Tople, Lukas Wutschitz, and Santiago Zanella-Béguelin · 2023
Cited alongside, same era.
Quantifying memorization across neural language models
Nicholas Carlini, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Florian Tramèr, and Chiyuan Zhang · 2023
Cited alongside, same era.
Delimiters won’t save you from prompt injection, 2023
Simon Willison · 2023
Cited alongside, same era.
Don’t you (forget nlp): Prompt injection with control characters in chatgpt
Win Suen Mark Breitenbach, Adrian Wood and Po-Ning Tseng · 2023
Cited alongside, same era.
Universal and transferable adversarial attacks on aligned language models
Stav Cohen, Ron Bitton, and Ben Nassi · 2024
Closest in time.
Bytedance coze, access in 2024
ByteDance · 2024
Closest in time.
Openai gpts, access in 2024
OpenAI · 2024
Closest in time.
Bytedance coze, access in 2024
ByteDance · 2024
Closest in time.
Formalizing and benchmarking prompt injection attacks and defenses
Yupei Liu, Yuqi Jia, Runpeng Geng, Jinyuan Jia, and Neil Zhenqiang Gong · 2024
Closest in time.
Tensor trust: Interpretable prompt injection attacks from an online game
Sam Toyer, Olivia Watkins, Ethan Adrian Mendes, Justin Svegliato, Luke Bailey, Tiffany Wang, Isaac Ong, Karim Elmaaroufi, Pieter Abbeel, Trevor Darrell, et al · 2024
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Andy Zou, Zifan Wang, Nicholas Carlini, Milad Nasr, J Zico Kolter, and Matt Fredrikson · 2023
Cited alongside, same era.
Prompts should not be seen as secrets: Systematically measuring prompt extraction attack success
Yiming Zhang and Daphne Ippolito · 2023
Cited alongside, same era.
Benchmarking and defending against indirect prompt injection attacks on large language models
Jingwei Yi, Yueqi Xie, Bin Zhu, Emre Kiciman, Guangzhong Sun, Xing Xie, and Fangzhao Wu · 2023
Cited alongside, same era.
Jailbreaking black box large language models in twenty queries
Patrick Chao, Alexander Robey, Edgar Dobriban, Hamed Hassani, George J Pappas, and Eric Wong · 2023
Cited alongside, same era.
Xinyue Shen, Zeyuan Chen, Michael Backes, Yun Shen, and Yang Zhang · 2023
Cited alongside, same era.
Wenjie Fu, Huandong Wang, Chen Gao, Guanghua Liu, Yong Li, and Tao Jiang · 2023
Cited alongside, same era.
Tensor trust: Interpretable prompt injection attacks from an online game
Sam Toyer, Olivia Watkins, Ethan Mendes, Justin Svegliato, Luke Bailey, Tiffany Wang, Isaac Ong, Karim Elmaaroufi, Pieter Abbeel, Trevor Darrell, et al · 2023
Cited alongside, same era.
Closest in time.
Assessing prompt injection risks in 200+ custom gpts
Jiahao Yu, Yuhang Wu, Dong Shu, Mingyu Jin, Sabrina Yang, and Xinyu Xing · 2024
Closest in time.
A survey on large language model based autonomous agents
Lei Wang, Chen Ma, Xueyang Feng, Zeyu Zhang, Hao Yang, Jingsen Zhang, Zhiyuan Chen, Jiakai Tang, Xu Chen, Yankai Lin, et al · 2024
Closest in time.
Autogen: Enabling next-gen llm applications via multi-agent conversation
Qingyun Wu, Gagan Bansal, Jieyu Zhang, Yiran Wu, Beibin Li, Erkang Zhu, Li Jiang, Xiaoyun Zhang, Shaokun Zhang, Jiale Liu, et al · 2024
Closest in time.
Langchain, access in 2024
LangChain · 2024
Closest in time.
Pleak: Prompt leaking attacks against large language model applications
Bo Hui, Haolin Yuan, Neil Gong, Philippe Burlina, and Yinzhi Cao · 2024
Closest in time.
Optimization-based prompt injection attack to llm-as-a-judge
Jiawen Shi, Zenghui Yuan, Yinuo Liu, Yue Huang, Pan Zhou, Lichao Sun, and Neil Zhenqiang Gong · 2024
Closest in time.
Automatic and universal prompt injection attacks against large language models
Xiaogeng Liu, Zhiyuan Yu, Yizhe Zhang, Ning Zhang, and Chaowei Xiao · 2024
Closest in time.
Struq: Defending against prompt injection with structured queries
Sizhe Chen, Julien Piet, Chawin Sitawarin, and David Wagner · 2024
Closest in time.
Are you still on track!? catching llm task drift with activations
Sahar Abdelnabi, Aideen Fay, Giovanni Cherubin, Ahmed Salem, Mario Fritz, and Andrew Paverd · 2024
Closest in time.
The instruction hierarchy: Training llms to prioritize privileged instructions
Eric Wallace, Kai Xiao, Reimar Leike, Lilian Weng, Johannes Heidecke, and Alex Beutel · 2024
Closest in time.
Propile: Probing privacy leakage in large language models
Siwon Kim, Sangdoo Yun, Hwaran Lee, Martin Gubri, Sungroh Yoon, and Seong Joon Oh · 2024
Closest in time.
Quantifying association capabilities of large language models and its implications on privacy leakage
Hanyin Shao, Jie Huang, Shen Zheng, and Kevin Chang · 2024
Closest in time.
Semantic-guided prompt organization for universal goal hijacking against llms
Yihao Huang, Chong Wang, Xiaojun Jia, Qing Guo, Felix Juefei-Xu, Jian Zhang, Geguang Pu, and Yang Liu · 2024
Closest in time.
Prsa: Prompt reverse stealing attacks against large language models
Yong Yang, Xuhong Zhang, Yi Jiang, Xi Chen, Haoyu Wang, Shouling Ji, and Zonghui Wang · 2024
Closest in time.
Masterkey: Automated jailbreaking of large language model chatbots
Gelei Deng, Yi Liu, Yuekang Li, Kailong Wang, Ying Zhang, Zefeng Li, Haoyu Wang, Tianwei Zhang, and Yang Liu · 2024
Closest in time.
Great, now write an article about that: The crescendo multi-turn llm jailbreak attack
Mark Russinovich, Ahmed Salem, and Ronen Eldan · 2024
Closest in time.
Privacy backdoors: Enhancing membership inference through poisoning pre-trained models
Yuxin Wen, Leo Marchyok, Sanghyun Hong, Jonas Geiping, Tom Goldstein, and Nicholas Carlini · 2024
Closest in time.
Data stealing attacks against large language models via backdooring
Jiaming He, Guanyu Hou, Xinyue Jia, Yangyang Chen, Wenqi Liao, Yinhang Zhou, and Rang Zhou · 2024
Closest in time.
Peizhuo Lv, Mengjie Sun, Hao Wang, Xiaofeng Wang, Shengzhi Zhang, Yuxuan Chen, Kai Chen, and Limin Sun · 2025
Closest in time.
Openai gpts, access in 2024
OpenAI · 2025
Closest in time.
A systematic survey of automatic prompt optimization techniques
Kiran Ramnath, Kang Zhou, Sheng Guan, Soumya Smruti Mishra, Xuan Qi, Zhengyuan Shen, Shuai Wang, Sangmin Woo, Sullam Jeoung, Yawei Wang, et al · 2025
Closest in time.