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The robustness of recent Large Language Models (LLMs) has become increasingly crucial as their applicability expands across various domains and real-world applications.
A fast and elitist multiobjective genetic algorithm: NSGA-II
Kalyanmoy Deb, Samir Agrawal, Amrit Pratap, and T. Meyarivan. 2002 · 2002
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Squad: 100, 000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension
Mandar Joshi, Eunsol Choi, Daniel S. Weld, and Luke Zettlemoyer. 2017 · 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 · 2018
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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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Wikiatomicedits: A multilingual corpus of wikipedia edits for modeling language and discourse
Manaal Faruqui, Ellie Pavlick, Ian Tenney, and Dipanjan Das. 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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Semantically equivalent adversarial rules for debugging NLP models
Marco Túlio Ribeiro, Sameer Singh, and Carlos Guestrin. 2018 · 2018
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Text processing like humans do: Visually attacking and shielding NLP systems
Steffen Eger, Gözde Gül Sahin, Andreas Rücklé, Ji-Ung Lee, Claudia Schulz, Mohsen Mesgar, Krishnkant Swarnkar, Edwin Simpson, and Iryna Gurevych. 2019 · 2019
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Natural questions: a benchmark for question answering research
Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur P. Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob Devlin, Kenton Lee, Kristina Toutanova, Llion Jones, Matthew Kelcey, Ming-Wei Chang, Andrew M. Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov. 2019 · 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 · 2020
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From hero to zéroe: A benchmark of low-level adversarial attacks
Steffen Eger and Yannik Benz. 2020 · 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 · 2020
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Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick S. H. Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
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Retrieval-augmented generation for knowledge-intensive NLP tasks
Patrick S. H. Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, and Douwe Kiela. 2020 · 2020
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Word-level textual adversarial attacking as combinatorial optimization
Yuan Zang, Fanchao Qi, Chenghao Yang, Zhiyuan Liu, Meng Zhang, Qun Liu, and Maosong Sun. 2020 · 2020
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Adversarial attacks on deep-learning models in natural language processing: A survey
Wei Emma Zhang, Quan Z. Sheng, Ahoud Alhazmi, and Chenliang Li. 2020 · 2020
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The web is your oyster - knowledge-intensive NLP against a very large web corpus
Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Dmytro Okhonko, Samuel Broscheit, Gautier Izacard, Patrick S. H. Lewis, Barlas Oguz, Edouard Grave, Wen-tau Yih, and Sebastian Riedel. 2021 · 2021
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BEIR: A heterogeneous benchmark for zero-shot evaluation of information retrieval models
Nandan Thakur, Nils Reimers, Andreas Rücklé, Abhishek Srivastava, and Iryna Gurevych. 2021 · 2021
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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 · 2021
Cited alongside, same era.
Towards improving adversarial training of NLP models
Jin Yong Yoo and Yanjun Qi. 2021a · 2021
Cited alongside, same era.
Towards improving adversarial training of NLP models
Jin Yong Yoo and Yanjun Qi. 2021b · 2021
Cited alongside, same era.
LangChain
Harrison Chase. 2022 · 2022
Cited alongside, same era.
GRS: combining generation and revision in unsupervised sentence simplification
Mohammad Dehghan, Dhruv Kumar, and Lukasz Golab. 2022 · 2022
Cited alongside, same era.
Unsupervised dense information retrieval with contrastive learning
Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, and Edouard Grave. 2022 · 2022
A survey on out-of-distribution evaluation of neural NLP models
Xinzhe Li, Ming Liu, Shang Gao, and Wray L. Buntine. 2023b · 2023
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When not to trust language models: Investigating effectiveness of parametric and non-parametric memories
Alex Mallen, Akari Asai, Victor Zhong, Rajarshi Das, Daniel Khashabi, and Hannaneh Hajishirzi. 2023 · 2023
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Measuring and narrowing the compositionality gap in language models
Ofir Press, Muru Zhang, Sewon Min, Ludwig Schmidt, Noah A. Smith, and Mike Lewis. 2023 · 2023
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Nomiracl: Knowing when you don’t know for robust multilingual retrieval-augmented generation
Nandan Thakur, Luiz Bonifacio, Xinyu Zhang, Odunayo Ogundepo, Ehsan Kamalloo, David Alfonso-Hermelo, Xiaoguang Li, Qun Liu, Boxing Chen, Mehdi Rezagholizadeh, and Jimmy Lin. 2023 · 2023
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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, Dan Bikel, Lukas Blecher, Cristian Canton-Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller, Cynthia Gao, Vedanuj Goswami, Naman Goyal, Anthony Hartshorn, Saghar Hosseini, Rui Hou, Hakan Inan, Marcin Kardas, Viktor Kerkez, Madian Khabsa, Isabel Kloumann, Artem Korenev, Punit Singh Koura, Marie-Anne Lachaux, Thibaut Lavril, Jenya Lee, Diana Liskovich, Yinghai Lu, Yuning Mao, Xavier Martinet, Todor Mihaylov, Pushkar Mishra, Igor Molybog, Yixin Nie, Andrew Poulton, Jeremy Reizenstein, Rashi Rungta, Kalyan Saladi, Alan Schelten, Ruan Silva, Eric Michael Smith, Ranjan Subramanian, Xiaoqing Ellen Tan, Binh Tang, Ross Taylor, Adina Williams, Jian Xiang Kuan, Puxin Xu, Zheng Yan, Iliyan Zarov, Yuchen Zhang, Angela Fan, Melanie Kambadur, Sharan Narang, Aurélien Rodriguez, Robert Stojnic, Sergey Edunov, and Thomas Scialom. 2023 · 2023
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Cited alongside, same era.
Internet-augmented language models through few-shot prompting for open-domain question answering
Angeliki Lazaridou, Elena Gribovskaya, Wojciech Stokowiec, and Nikolai Grigorev. 2022 · 2022
Cited alongside, same era.
Perturbations in the wild: Leveraging human-written text perturbations for realistic adversarial attack and defense
Thai Le, Jooyoung Lee, Kevin Yen, Yifan Hu, and Dongwon Lee. 2022 · 2022
Cited alongside, same era.
LlamaIndex
Jerry Liu. 2022 · 2022
Cited alongside, same era.
Knowledge-augmented language model verification
Jinheon Baek, Soyeong Jeong, Minki Kang, Jong C. Park, and Sung Ju Hwang. 2023 · 2023
Cited alongside, same era.
Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing. 2023 · 2023
Cited alongside, same era.
Improving zero-shot reader by reducing distractions from irrelevant documents in open-domain question answering
Sukmin Cho, Jeongyeon Seo, Soyeong Jeong, and Jong C. Park. 2023 · 2023
Cited alongside, same era.
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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 · 2023
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Black-box sparse adversarial attack via multi-objective optimisation CVPR proceedings
Phoenix Neale Williams and Ke Li. 2023 · 2023
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Poisoning retrieval corpora by injecting adversarial passages
Zexuan Zhong, Ziqing Huang, Alexander Wettig, and Danqi Chen. 2023 · 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 · 2023
Later among the works it cites.
Self-RAG: Learning to retrieve, generate, and critique through self-reflection
Akari Asai, Zeqiu Wu, Yizhong Wang, Avirup Sil, and Hannaneh Hajishirzi. 2024 · 2024
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Benchmarking large language models in retrieval-augmented generation
Jiawei Chen, Hongyu Lin, Xianpei Han, and Le Sun. 2024 · 2024
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The power of noise: Redefining retrieval for RAG systems
Florin Cuconasu, Giovanni Trappolini, Federico Siciliano, Simone Filice, Cesare Campagnano, Yoelle Maarek, Nicola Tonellotto, and Fabrizio Silvestri. 2024 · 2024
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Adaptive-RAG: Learning to adapt retrieval-augmented large language models through question complexity
Soyeong Jeong, Jinheon Baek, Sukmin Cho, Sung Ju Hwang, and Jong C. Park. 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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ToolLLM: Facilitating large language models to master 16000+ real-world APIs
Yujia Qin, Shihao Liang, Yining Ye, Kunlun Zhu, Lan Yan, Yaxi Lu, Yankai Lin, Xin Cong, Xiangru Tang, Bill Qian, Sihan Zhao, Lauren Hong, Runchu Tian, Ruobing Xie, Jie Zhou, Mark Gerstein, dahai li, Zhiyuan Liu, and Maosong Sun. 2024 · 2024
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REAR: A relevance-aware retrieval-augmented framework for open-domain question answering
Yuhao Wang, Ruiyang Ren, Junyi Li, Wayne Xin Zhao, Jing Liu, and Ji-Rong Wen. 2024 · 2024
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Making retrieval-augmented language models robust to irrelevant context
Ori Yoran, Tomer Wolfson, Ori Ram, and Jonathan Berant. 2024 · 2024
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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. 2024 · 2024
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