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We design, implement, and evaluate adversarial decoding, a new, generic text generation technique that produces readable documents for different adversarial objectives.
FreeLB: Enhanced adversarial training for natural language understanding
Chen Zhu, Yu Cheng, Zhe Gan, Siqi Sun, Tom Goldstein, and Jingjing Liu. 2019 · 1909
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MS MARCO: A human generated machine reading comprehension dataset
Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, et al. 2016 · 2016
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HotFlip: White-box adversarial examples for text classification
Javid Ebrahimi, Anyi Rao, Daniel Lowd, and Dejing Dou. 2018 · 2018
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
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TweetEval: Unified benchmark and comparative evaluation for tweet classification
Francesco Barbieri, Jose Camacho-Collados, Luis Espinosa Anke, and Leonardo Neves. 2020 · 2020
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HAL: Improved text-image matching by mitigating visual semantic hubs
Fangyu Liu, Rongtian Ye, Xun Wang, and Shuaipeng Li. 2020 · 2020
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Reevaluating adversarial examples in natural language
John X Morris, Eli Lifland, Jack Lanchantin, Yangfeng Ji, and Yanjun Qi. 2020 · 2020
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Adversarial semantic collisions
Congzheng Song, Alexander M Rush, and Vitaly Shmatikov. 2020 · 2020
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MiniLM: Deep self-attention distillation for task-agnostic compression of pre-trained transformers
Wenhui Wang, Furu Wei, Li Dong, Hangbo Bao, Nan Yang, and Ming Zhou. 2020 · 2020
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Neurologic decoding: (un)supervised neural text generation with predicate logic constraints
Ximing Lu, Peter West, Rowan Zellers, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. 2021 · 2021
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Unsupervised dense information retrieval with contrastive learning
Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, and Edouard Grave. 2022 · 2022
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MTEB: Massive text embedding benchmark
Niklas Muennighoff, Nouamane Tazi, Loïc Magne, and Nils Reimers. 2022 · 2022
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Sentence-T5: Scalable sentence encoders from pre-trained text-to-text models
Jianmo Ni, Gustavo Hernandez Abrego, Noah Constant, Ji Ma, Keith B Hall, Daniel Cer, and Yinfei Yang. 2022 · 2022
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COLD decoding: Energy-based constrained text generation with Langevin dynamics
Lianhui Qin, Sean Welleck, Daniel Khashabi, and Yejin Choi. 2022 · 2022
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Jailbreaking black box large language models in twenty queries
Patrick Chao, Alexander Robey, Edgar Dobriban, Hamed Hassani, George J Pappas, and Eric Wong. 2023 · 2023
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Llama Guard: LLM-based input-output safeguard for human-AI conversations
Hakan Inan, Kartikeya Upasani, Jianfeng Chi, Rashi Rungta, Krithika Iyer, Yuning Mao, Michael Tontchev, Qing Hu, Brian Fuller, Davide Testuggine, et al. 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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Towards general text embeddings with multi-stage contrastive learning
Zehan Li, Xin Zhang, Yanzhao Zhang, Dingkun Long, Pengjun Xie, and Meishan Zhang. 2023 · 2023
Cited alongside, same era.
AutoDAN: Generating stealthy jailbreak prompts on aligned large language models
Xiaogeng Liu, Nan Xu, Muhao Chen, and Chaowei Xiao. 2023 · 2023
Cited alongside, same era.
COLD-Attack: Jailbreaking LLMs with stealthiness and controllability
Xingang Guo, Fangxu Yu, Huan Zhang, Lianhui Qin, and Bin Hu. 2024 · 2024
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Exploring backdoor attacks against large language model-based decision making
Ruochen Jiao, Shaoyuan Xie, Justin Yue, Takami Sato, Lixu Wang, Yixuan Wang, Qi Alfred Chen, and Qi Zhu. 2024 · 2024
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AutoDAN-Turbo: A lifelong agent for strategy self-exploration to jailbreak llms
Xiaogeng Liu, Peiran Li, Edward Suh, Yevgeniy Vorobeychik, Zhuoqing Mao, Somesh Jha, Patrick McDaniel, Huan Sun, Bo Li, and Chaowei Xiao. 2024 · 2024
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Backdoor attacks on dense passage retrievers for disseminating misinformation
Quanyu Long, Yue Deng, LeiLei Gan, Wenya Wang, and Sinno Jialin Pan. 2024 · 2024
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HarmBench: A standardized evaluation framework for automated red teaming and robust refusal
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Xiangyu Qi, Yi Zeng, Tinghao Xie, Pin-Yu Chen, Ruoxi Jia, Prateek Mittal, and Peter Henderson. 2023 · 2023
Cited alongside, same era.
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 · 2023
Cited alongside, same era.
Llama 2: Open foundation and fine-tuned chat models
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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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
Cited alongside, same era.
Poisoning retrieval corpora by injecting adversarial passages
Zexuan Zhong, Ziqing Huang, Alexander Wettig, and Danqi Chen. 2023 · 2023
Cited alongside, same era.
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
Cited alongside, same era.
Jailbreaking leading safety-aligned LLMs with simple adaptive attacks
Maksym Andriushchenko, Francesco Croce, and Nicolas Flammarion. 2024 · 2024
Cited alongside, same era.
Phantom: General trigger attacks on retrieval augmented language generation
Harsh Chaudhari, Giorgio Severi, John Abascal, Matthew Jagielski, Christopher A Choquette-Choo, Milad Nasr, Cristina Nita-Rotaru, and Alina Oprea. 2024 · 2024
Cited alongside, same era.
Mantas Mazeika, Long Phan, Xuwang Yin, Andy Zou, Zifan Wang, Norman Mu, Elham Sakhaee, Nathaniel Li, Steven Basart, Bo Li, et al. 2024 · 2024
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Fast adversarial attacks on language models in one GPU minute
Vinu Sankar Sadasivan, Shoumik Saha, Gaurang Sriramanan, Priyatham Kattakinda, Atoosa Chegini, and Soheil Feizi. 2024 · 2024
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Gemma 2: Improving open language models at a practical size
Gemma Team, Morgane Riviere, Shreya Pathak, Pier Giuseppe Sessa, Cassidy Hardin, Surya Bhupatiraju, Léonard Hussenot, Thomas Mesnard, Bobak Shahriari, Alexandre Ramé, et al. 2024 · 2024
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Certifiably robust RAG against retrieval corruption
Chong Xiang, Tong Wu, Zexuan Zhong, David Wagner, Danqi Chen, and Prateek Mittal. 2024 · 2024
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BadRAG: Identifying vulnerabilities in retrieval augmented generation of large language models
Jiaqi Xue, Mengxin Zheng, Yebowen Hu, Fei Liu, Xun Chen, and Qian Lou. 2024 · 2024
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An Yang, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chengyuan Li, Dayiheng Liu, Fei Huang, Haoran Wei, et al. 2024 · 2024
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AutoDAN: interpretable gradient-based adversarial attacks on large language models
Sicheng Zhu, Ruiyi Zhang, Bang An, Gang Wu, Joe Barrow, Zichao Wang, Furong Huang, Ani Nenkova, and Tong Sun. 2024 · 2024
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Misinformation fake news text dataset 79k
Steven Peutz. 2023 · 2025
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Machine against the RAG: Jamming retrieval-augmented generation with blocker documents
Avital Shafran, Roei Schuster, and Vitaly Shmatikov. 2025 · 2025
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PoisonedRAG: Knowledge poisoning attacks to retrieval-augmented generation of large language models
Wei Zou, Runpeng Geng, Binghui Wang, and Jinyuan Jia. 2025 · 2025
Closest in time.