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Large Language Models (LLMs) undergo continuous updates to improve user experience.
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
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Crafting Adversarial Input Sequences for Recurrent Neural Networks
Nicolas Papernot, Patrick D. McDaniel, Ananthram Swami, and Richard E. Harang · 2016
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Get To The Point: Summarization with Pointer-Generator Networks
Abigail See, Peter J. Liu, and Christopher D. Manning · 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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Bilateral Multi-Perspective Matching for Natural Language Sentences
Zhiguo Wang, Wael Hamza, and Radu Florian · 2017
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Generating Natural Language Adversarial Examples
Moustafa Alzantot, Yash Sharma, Ahmed Elgohary, Bo-Jhang Ho, Mani B. Srivastava, and Kai-Wei Chang · 2018
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Synthetic and Natural Noise Both Break Neural Machine Translation
Yonatan Belinkov and Yonatan Bisk · 2018
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Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning
Hongge Chen, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, and Cho-Jui Hsieh · 2018
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HotFlip: White-Box Adversarial Examples for Text Classification
Javid Ebrahimi, Anyi Rao, Daniel Lowd, and Dejing Dou · 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
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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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Deep Text Classification Can be Fooled
Bin Liang, Hongcheng Li, Miaoqiang Su, Pan Bian, Xirong Li, and Wenchang Shi · 2018
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Adversarially Regularising Neural NLI Models to Integrate Logical Background Knowledge
Pasquale Minervini and Sebastian Riedel · 2018
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Stress Test Evaluation for Natural Language Inference
Aakanksha Naik, Abhilasha Ravichander, Norman M. Sadeh, Carolyn P. Rosé, and Graham Neubig · 2018
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Semantically Equivalent Adversarial Rules for Debugging NLP models
Marco Túlio Ribeiro, Sameer Singh, and Carlos Guestrin · 2018
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Generating Adversarial Text Samples
Suranjana Samanta and Sameep Mehta · 2018
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Adafactor: Adaptive Learning Rates with Sublinear Memory Cost
Noam Shazeer and Mitchell Stern · 2018
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A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference
Adina Williams, Nikita Nangia, and Samuel R. Bowman · 2018
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Fooling Vision and Language Models Despite Localization and Attention Mechanism
Xiaojun Xu, Xinyun Chen, Chang Liu, Anna Rohrbach, Trevor Darrell, and Dawn Song · 2018
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HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W. Cohen, Ruslan Salakhutdinov, and Christopher D. Manning · 2018
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TextBugger: Generating Adversarial Text Against Real-world Applications
Jinfeng Li, Shouling Ji, Tianyu Du, Bo Li, and Ting Wang · 2019
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OpenDialKG: Explainable Conversational Reasoning with Attention-based Walks over Knowledge Graphs
Seungwhan Moon, Pararth Shah, Anuj Kumar, and Rajen Subba · 2019
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GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman · 2019
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Zero-Shot Learning - A Comprehensive Evaluation of the Good, the Bad and the Ugly
Yongqin Xian, Christoph H. Lampert, Bernt Schiele, and Zeynep Akata · 2019
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Language Models are Few-Shot Learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 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
Cited alongside, same era.
BERT-ATTACK: Adversarial Attack Against BERT Using BERT
Linyang Li, Ruotian Ma, Qipeng Guo, Xiangyang Xue, and Xipeng Qiu · 2020
Yunjie Ji, Yong Deng, Yan Gong, Yiping Peng, Qiang Niu, Lei Zhang, Baochang Ma, and Xiangang Li · 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, élio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed · 2023
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Is ChatGPT A Good Translator? A Preliminary Study
Wenxiang Jiao, Wenxuan Wang, Jen-tse Huang, Xing Wang, and Zhaopeng Tu · 2023
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Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks
Daniel Kang, Xuechen Li, Ion Stoica, Carlos Guestrin, Matei Zaharia, and Tatsunori Hashimoto · 2023
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Cited alongside, same era.
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu · 2020
Cited alongside, same era.
Beyond Accuracy: Behavioral Testing of NLP Models with CheckList
Marco Túlio Ribeiro, Tongshuang Wu, Carlos Guestrin, and Sameer Singh · 2020
Cited alongside, same era.
Adversarial Attacks on Deep-learning Models in Natural Language Processing: A Survey
Wei Emma Zhang, Quan Z. Sheng, Ahoud Alhazmi, and Chenliang Li · 2020
Cited alongside, same era.
Persistent Anti-Muslim Bias in Large Language Models
Abubakar Abid, Maheen Farooqi, and James Zou · 2021
Cited alongside, same era.
Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models
Boxin Wang, Chejian Xu, Shuohang Wang, Zhe Gan, Yu Cheng, Jianfeng Gao, Ahmed Hassan Awadallah, and Bo Li · 2021
Cited alongside, same era.
LoRA: Low-Rank Adaptation of Large Language Models
Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 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.
HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models
Junyi Li, Xiaoxue Cheng, Xin Zhao, Jian-Yun Nie, and Ji-Rong Wen · 2023
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SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models
Potsawee Manakul, Adian Liusie, and Mark J. F. Gales · 2023
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Tree of Attacks: Jailbreaking Black-Box LLMs Automatically
Anay Mehrotra, Manolis Zampetakis, Paul Kassianik, Blaine Nelson, Hyrum Anderson, Yaron Singer, and Amin Karbasi · 2023
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What In-Context Learning "Learns" In-Context: Disentangling Task Recognition and Task Learning
Jane Pan, Tianyu Gao, Howard Chen, and Danqi Chen · 2023
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On the Risk of Misinformation Pollution with Large Language Models
Yikang Pan, Liangming Pan, Wenhu Chen, Preslav Nakov, Min-Yen Kan, and William Yang Wang · 2023
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Xinyue Shen, Zeyuan Chen, Michael Backes, Yun Shen, and Yang Zhang · 2023
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Text Classification via Large Language Models
Xiaofei Sun, Xiaoya Li, Jiwei Li, Fei Wu, Shangwei Guo, Tianwei Zhang, and Guoyin Wang · 2023
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Miles Turpin, Julian Michael, Ethan Perez, and Samuel R. Bowman · 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
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On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective
Jindong Wang, Xixu Hu, Wenxin Hou, Hao Chen, Runkai Zheng, Yidong Wang, Linyi Yang, Haojun Huang, Wei Ye, Xiubo Geng, Binxing Jiao, Yue Zhang, and Xing Xie · 2023
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GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts
Jiahao Yu, Xingwei Lin, Zheng Yu, and Xinyu Xing · 2023
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Don’t Make Your LLM an Evaluation Benchmark Cheater
Kun Zhou, Yutao Zhu, Zhipeng Chen, Wentong Chen, Wayne Xin Zhao, Xu Chen, Yankai Lin, Ji-Rong Wen, and Jiawei Han · 2023
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Context-faithful Prompting for Large Language Models
Wenxuan Zhou, Sheng Zhang, Hoifung Poon, and Muhao Chen · 2023
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MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models
Deyao Zhu, Jun Chen, Xiaoqian Shen, Xiang Li, and Mohamed Elhoseiny · 2023
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PromptBench: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts
Kaijie Zhu, Jindong Wang, Jiaheng Zhou, Zichen Wang, Hao Chen, Yidong Wang, Linyi Yang, Wei Ye, Neil Zhenqiang Gong, Yue Zhang, and Xing Xie · 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
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Comprehensive Assessment of Jailbreak Attacks Against LLMs
Junjie Chu, Yugeng Liu, Ziqing Yang, Xinyue Shen, Michael Backes, and Yang Zhang · 2024
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Weak-to-Strong Jailbreaking on Large Language Models
Xuandong Zhao, Xianjun Yang, Tianyu Pang, Chao Du, Lei Li, Yu-Xiang Wang, and William Yang Wang · 2024
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