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Large Language Models (LLMs) are powerful zero-shot assessors used in real-world situations such as assessing written exams and benchmarking systems.
Natural language adversarial attacks and defenses in word level
Xiaosen Wang, Hao Jin, and Kun He. 2019 · 1909
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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METEOR: An automatic metric for MT evaluation with improved correlation with human judgments
Satanjeev Banerjee and Alon Lavie. 2005 · 2005
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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. 2020 · 2012
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus. 2014 · 2014
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Explaining and harnessing adversarial examples
Ian J. Goodfellow, Jonathon Shlens, and Christian Szegedy. 2015 · 2015
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Delving into transferable adversarial examples and black-box attacks
Yanpei Liu, Xinyun Chen, Chang Liu, and Dawn Song. 2016 · 2016
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Practical black-box attacks against deep learning systems using adversarial examples
Nicolas Papernot, Patrick D. McDaniel, Ian J. Goodfellow, Somesh Jha, Z. Berkay Celik, and Ananthram Swami. 2016 · 2016
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Generating natural language adversarial examples
Moustafa Alzantot, Yash Sharma, Ahmed Elgohary, Bo-Jhang Ho, Mani Srivastava, and Kai-Wei Chang. 2018 · 2018
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Black-box generation of adversarial text sequences to evade deep learning classifiers
Ji Gao, Jack Lanchantin, Mary Lou Soffa, and Yanjun Qi. 2018 · 2018
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Topical-Chat: Towards Knowledge-Grounded Open-Domain Conversations
Karthik Gopalakrishnan, Behnam Hedayatnia, Qinlang Chen, Anna Gottardi, Sanjeev Kwatra, Anu Venkatesh, Raefer Gabriel, and Dilek Hakkani-Tür. 2019 · 2019
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Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi. 2019 · 2019
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BAE: BERT-based adversarial examples for text classification
Siddhant Garg and Goutham Ramakrishnan. 2020 · 2020
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BERT-ATTACK: Adversarial attack against BERT using BERT
Linyang Li, Ruotian Ma, Qipeng Guo, Xiangyang Xue, and Xipeng Qiu. 2020 · 2020
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Unsupervised evaluation of interactive dialog with DialoGPT
Shikib Mehri and Maxine Eskenazi. 2020 · 2020
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Universal Adversarial Attacks on Spoken Language Assessment Systems
Vyas Raina, Mark J.F. Gales, and Kate M. Knill. 2020 · 2020
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Comet: A neural framework for mt evaluation
Ricardo Rei, Craig Stewart, Ana C Farinha, and Alon Lavie. 2020 · 2020
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Asking and answering questions to evaluate the factual consistency of summaries
Alex Wang, Kyunghyun Cho, and Mike Lewis. 2020 · 2020
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Summeval: Re-evaluating summarization evaluation
Alexander R Fabbri, Wojciech Kryściński, Bryan McCann, Caiming Xiong, Richard Socher, and Dragomir Radev. 2021 · 2021
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Scaling instruction-finetuned language models
Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Yunxuan Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, et al. 2022 · 2022
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Are aligned neural networks adversarially aligned?
Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, Matthew Jagielski, Irena Gao, Anas Awadalla, Pang Wei Koh, Daphne Ippolito, Katherine Lee, Florian Tramer, and Ludwig Schmidt. 2023 · 2023
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Jailbreaking black box large language models in twenty queries
Large language models are effective text rankers with pairwise ranking prompting
Zhen Qin, Rolf Jagerman, Kai Hui, Honglei Zhuang, Junru Wu, Jiaming Shen, Tianqi Liu, Jialu Liu, Donald Metzler, Xuanhui Wang, and Michael Bendersky. 2023 · 2023
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Sentiment perception adversarial attacks on neural machine translation systems
Vyas Raina and Mark Gales. 2023 · 2023
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Smoothllm: Defending large language models against jailbreaking attacks
Alexander Robey, Eric Wong, Hamed Hassani, and George J. Pappas. 2023 · 2023
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A classification-guided approach for adversarial attacks against neural machine translation
Sahar Sadrizadeh, Ljiljana Dolamic, and Pascal Frossard. 2023 · 2023
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Patrick Chao, Alexander Robey, Edgar Dobriban, Hamed Hassani, George J. Pappas, and Eric Wong. 2023 · 2023
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Exploring the use of large language models for reference-free text quality evaluation: An empirical study
Yi Chen, Rui Wang, Haiyun Jiang, Shuming Shi, and Ruifeng Xu. 2023 · 2023
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Gptscore: Evaluate as you desire
Jinlan Fu, See-Kiong Ng, Zhengbao Jiang, and Pengfei Liu. 2023 · 2023
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Baseline defenses for adversarial attacks against aligned language models
Neel Jain, Avi Schwarzschild, Yuxin Wen, Gowthami Somepalli, John Kirchenbauer, Ping yeh Chiang, Micah Goldblum, Aniruddha Saha, Jonas Geiping, and Tom Goldstein. 2023 · 2023
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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 · 2023
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Benchmarking cognitive biases in large language models as evaluators
Ryan Koo, Minhwa Lee, Vipul Raheja, Jong Inn Park, Zae Myung Kim, and Dongyeop Kang. 2023 · 2023
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Open sesame! universal black box jailbreaking of large language models
Raz Lapid, Ron Langberg, and Moshe Sipper. 2023 · 2023
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G-eval: NLG evaluation using gpt-4 with better human alignment
Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, and Chenguang Zhu. 2023b · 2023
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Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al. 2023 · 2023
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Jailbroken: How does llm safety training fail?
Alexander Wei, Nika Haghtalab, and Jacob Steinhardt. 2023 · 2023
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A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, Yifan Du, Chen Yang, Yushuo Chen, Zhipeng Chen, Jinhao Jiang, Ruiyang Ren, Yifan Li, Xinyu Tang, Zikang Liu, Peiyu Liu, Jian-Yun Nie, and Ji-Rong Wen. 2023 · 2023
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Judging llm-as-a-judge with mt-bench and chatbot arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric Xing, et al. 2023 · 2023
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Universal and transferable adversarial attacks on aligned language models
Andy Zou, Zifan Wang, Nicholas Carlini, Milad Nasr, J. Zico Kolter, and Matt Fredrikson. 2023 · 2023
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Catastrophic jailbreak of open-source LLMs via exploiting generation
Yangsibo Huang, Samyak Gupta, Mengzhou Xia, Kai Li, and Danqi Chen. 2024 · 2024
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Haibo Jin, Ruoxi Chen, Andy Zhou, Jinyin Chen, Yang Zhang, and Haohan Wang. 2024 · 2024
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Certifying llm safety against adversarial prompting
Aounon Kumar, Chirag Agarwal, Suraj Srinivas, Aaron Jiaxun Li, Soheil Feizi, and Himabindu Lakkaraju. 2024 · 2024
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Yi Zeng, Hongpeng Lin, Jingwen Zhang, Diyi Yang, Ruoxi Jia, and Weiyan Shi. 2024 · 2024
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Robust prompt optimization for defending language models against jailbreaking attacks
Andy Zhou, Bo Li, and Haohan Wang. 2024 · 2024
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AutoDAN: Automatic and interpretable adversarial attacks on large language models
Sicheng Zhu, Ruiyi Zhang, Bang An, Gang Wu, Joe Barrow, Furong Huang, and Tong Sun. 2024 · 2024
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Towards a unified multi-dimensional evaluator for text generation
Ming Zhong, Yang Liu, Da Yin, Yuning Mao, Yizhu Jiao, Pengfei Liu, Chenguang Zhu, Heng Ji, and Jiawei Han. 2022b · 2038
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