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The misuse of large language models (LLMs) has drawn significant attention from the general public and LLM vendors.
Modularity and community structure in networks
Mark E. J. Newman · 2006
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Generalized Louvain method for community detection in large networks
Pasquale De Meo, Emilio Ferrara, Giacomo Fiumara, and Alessandro Provetti · 2011
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Ethical research standards in a world of big data
Caitlin M. Rivers and Bryan L. Lewis · 2014
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Fleiss’ kappa statistic without paradoxes
Rosa Falotico and Piero Quatto · 2015
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Deep Reinforcement Learning from Human Preferences
Paul F. Christiano, Jan Leike, Tom B. Brown, Miljan Martic, Shane Legg, and Dario Amodei · 2017
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Attention is All you Need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Adversarial Example Generation with Syntactically Controlled Paraphrase Networks
Mohit Iyyer, John Wieting, Kevin Gimpel, and Luke Zettlemoyer · 2018
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UMAP: Uniform Manifold Approximation and Projection
Leland McInnes, John Healy, Nathaniel Saul, and Lukas Großberger · 2018
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Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
Nils Reimers and Iryna Gurevych · 2019
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The Pushshift Reddit Dataset
Jason Baumgartner, Savvas Zannettou, Brian Keegan, Megan Squire, and Jeremy Blackburn · 2020
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Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment
Di Jin, Zhijing Jin, Joey Tianyi Zhou, and Peter Szolovits · 2020
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“And We Will Fight For Our Race!” A Measurement Study of Genetic Testing Conversations on Reddit and 4chan
Alexandros Mittos, Savvas Zannettou, Jeremy Blackburn, and Emiliano De Cristofaro · 2020
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Beyond Accuracy: Behavioral Testing of NLP Models with CheckList
Marco Túlio Ribeiro, Tongshuang Wu, Carlos Guestrin, and Sameer Singh · 2020
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Learning to summarize from human feedback
Nisan Stiennon, Long Ouyang, Jeff Wu, Daniel M. Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, and Paul F. Christiano · 2020
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OPUS-MT - Building open translation services for the World
Jörg Tiedemann and Santhosh Thottingal · 2020
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A Quantitative Approach to Understanding Online Antisemitism
Savvas Zannettou, Joel Finkelstein, Barry Bradlyn, and Jeremy Blackburn · 2020
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Extracting Training Data from Large Language Models
Nicholas Carlini, Florian Tramèr, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom B. Brown, Dawn Song, Úlfar Erlingsson, Alina Oprea, and Colin Raffel · 2021
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BadNL: Backdoor Attacks Against NLP Models with Semantic-preserving Improvements
Xiaoyi Chen, Ahmed Salem, Michael Backes, Shiqing Ma, Qingni Shen, Zhonghai Wu, and Yang Zhang · 2021
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PalmTree: Learning an Assembly Language Model for Instruction Embedding
Xuezixiang Li, Yu Qu, and Heng Yin · 2021
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Detecting AI Trojans Using Meta Neural Analysis
Xiaojun Xu, Qi Wang, Huichen Li, Nikita Borisov, Carl A. Gunter, and Bo Li · 2021
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Spinning Language Models: Risks of Propaganda-As-A-Service and Countermeasures
Eugene Bagdasaryan and Vitaly Shmatikov · 2022
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Bad Characters: Imperceptible NLP Attacks
Nicholas Boucher, Ilia Shumailov, Ross Anderson, and Nicolas Papernot · 2022
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GLM: General Language Model Pretraining with Autoregressive Blank Infilling
Zhengxiao Du, Yujie Qian, Xiao Liu, Ming Ding, Jiezhong Qiu, Zhilin Yang, and Jie Tang · 2022
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A Holistic Approach to Undesired Content Detection in the Real World
Todor Markov, Chong Zhang, Sandhini Agarwal, Tyna Eloundou, Teddy Lee, Steven Adler, Angela Jiang, and Lilian Weng · 2022
Cited alongside, same era.
Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?
Sewon Min, Xinxi Lyu, Ari Holtzman, Mikel Artetxe, Mike Lewis, Hannaneh Hajishirzi, and Luke Zettlemoyer · 2022
Cited alongside, same era.
DeepPhish: Understanding User Trust Towards Artificially Generated Profiles in Online Social Networks
Jaron Mink, Licheng Luo, Natã M. Barbosa, Olivia Figueira, Yang Wang, and Gang Wang · 2022
Cited alongside, same era.
Quantifying Privacy Risks of Masked Language Models Using Membership Inference Attacks
Fatemehsadat Mireshghallah, Kartik Goyal, Archit Uniyal, Taylor Berg-Kirkpatrick, and Reza Shokri · 2022
Cited alongside, same era.
Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul F. Christiano, Jan Leike, and Ryan Lowe · 2022
On the Reliability of Watermarks for Large Language Models
John Kirchenbauer, Jonas Geiping, Yuxin Wen, Manli Shu, Khalid Saifullah, Kezhi Kong, Kasun Fernando, Aniruddha Saha, Micah Goldblum, and Tom Goldstein · 2023
Closest in time.
Multi-step Jailbreaking Privacy Attacks on ChatGPT
Haoran Li, Dadi Guo, Wei Fan, Mingshi Xu, and Yangqiu Song · 2023
Closest in time.
Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig · 2023
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Jailbreaking ChatGPT via Prompt Engineering: An Empirical Study
Yi Liu, Gelei Deng, Zhengzi Xu, Yuekang Li, Yaowen Zheng, Ying Zhang, Lida Zhao, Tianwei Zhang, and Yang Liu · 2023
Closest in time.
Analyzing Leakage of Personally Identifiable Information in Language Models
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Cited alongside, same era.
Ignore Previous Prompt: Attack Techniques For Language Models
Fábio Perez and Ian Ribeiro · 2022
Cited alongside, same era.
Why So Toxic? Measuring and Triggering Toxic Behavior in Open-Domain Chatbots
Wai Man Si, Michael Backes, Jeremy Blackburn, Emiliano De Cristofaro, Gianluca Stringhini, Savvas Zannettou, and Yang Zhang · 2022
Cited alongside, same era.
Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets
Florian Tramèr, Reza Shokri, Ayrton San Joaquin, Hoang Le, Matthew Jagielski, Sanghyun Hong, and Nicholas Carlini · 2022
Cited alongside, same era.
http://www.cac.gov.cn/2023-07/13/c_1690898327029107.htm
Measures for the Management of Generative Artificial Intelligence Services · 2023
Cited alongside, same era.
Meysam Alizadeh, Maël Kubli, Zeynab Samei, Shirin Dehghani, Juan Diego Bermeo, Maria Korobeynikova, and Fabrizio Gilardi · 2023
Cited alongside, same era.
Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, Wenliang Dai, Dan Su, Bryan Wilie, Holy Lovenia, Ziwei Ji, Tiezheng Yu, Willy Chung, Quyet V. Do, Yan Xu, and Pascale Fung · 2023
Cited alongside, same era.
Beyond Phish: Toward Detecting Fraudulent e-Commerce Websites at Scale
Marzieh Bitaab, Haehyun Cho, Adam Oest, Zhuoer Lyu, Wei Wang, Jorij Abraham, Ruoyu Wang, Tiffany Bao, Yan Shoshitaishvili, and Adam Doupé · 2023
Cited alongside, same era.
Nils Lukas, Ahmed Salem, Robert Sim, Shruti Tople, Lukas Wutschitz, and Santiago Zanella Béguelin · 2023
Closest in time.
OpenAI · 2023
Closest in time.
To ChatGPT, or not to ChatGPT: That is the question!
Alessandro Pegoraro, Kavita Kumari, Hossein Fereidooni, and Ahmad-Reza Sadeghi · 2023
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Can Large Language Models Reason about Program Invariants?
Kexin Pei, David Bieber, Kensen Shi, Charles Sutton, and Pengcheng Yin · 2023
Closest in time.
Unsafe Diffusion: On the Generation of Unsafe Images and Hateful Memes From Text-To-Image Models
Yiting Qu, Xinyue Shen, Xinlei He, Michael Backes, Savvas Zannettou, and Yang Zhang · 2023
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On Second Thought, Let’s Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning
Omar Shaikh, Hongxin Zhang, William Held, Michael Bernstein, and Diyi Yang · 2023
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In ChatGPT We Trust? Measuring and Characterizing the Reliability of ChatGPT
Xinyue Shen, Zeyuan Chen, Michael Backes, and Yang Zhang · 2023
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LLaMA: Open and Efficient Foundation Language Models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurélien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample · 2023
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DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models
Boxin Wang, Weixin Chen, Hengzhi Pei, Chulin Xie, Mintong Kang, Chenhui Zhang, Chejian Xu, Zidi Xiong, Ritik Dutta, Rylan Schaeffer, Sang T. Truong, Simran Arora, Mantas Mazeika, Dan Hendrycks, Zinan Lin, Yu Cheng, Sanmi Koyejo, Dawn Song, and Bo Li · 2023
Closest in time.
WizMap: Scalable Interactive Visualization for Exploring Large Machine Learning Embeddings
Zijie J. Wang, Fred Hohman, and Duen Horng Chau · 2023
Closest in time.
Jailbroken: How Does LLM Safety Training Fail?
Alexander Wei, Nika Haghtalab, and Jacob Steinhardt · 2023
Closest in time.
CodeIPPrompt: Intellectual Property Infringement Assessment of Code Language Models
Zhiyuan Yu, Yuhao Wu, Ning Zhang, Chenguang Wang, Yevgeniy Vorobeychik, and Chaowei Xiao · 2023
Closest in time.
GLM-130B: An Open Bilingual Pre-trained Model
Aohan Zeng, Xiao Liu, Zhengxiao Du, Zihan Wang, Hanyu Lai, Ming Ding, Zhuoyi Yang, Yifan Xu, Wendi Zheng, Xiao Xia, Weng Lam Tam, Zixuan Ma, Yufei Xue, Jidong Zhai, Wenguang Chen, Zhiyuan Liu, Peng Zhang, Yuxiao Dong, and Jie Tang · 2023
Closest in time.
Synthetic Lies: Understanding AI-Generated Misinformation and Evaluating Algorithmic and Human Solutions
Jiawei Zhou, Yixuan Zhang, Qianni Luo, Andrea G. Parker, and Munmun De Choudhury · 2023
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Can ChatGPT Reproduce Human-Generated Labels? A Study of Social Computing Tasks
Yiming Zhu, Peixian Zhang, Ehsan ul Haq, Pan Hui, and Gareth Tyson · 2023
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Universal and Transferable Adversarial Attacks on Aligned Language Models
Andy Zou, Zifan Wang, J. Zico Kolter, and Matt Fredrikson · 2023
Closest in time.
Malla: Demystifying Real-world Large Language Model Integrated Malicious Services
Zilong Lin, Jian Cui, Xiaojing Liao, and XiaoFeng Wang · 2024
Closest in time.
Yi Zeng, Hongpeng Lin, Jingwen Zhang, Diyi Yang, Ruoxi Jia, and Weiyan Shi · 2024
Closest in time.