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Large language models (LLMs) have achieved remarkable performance in various natural language processing tasks, especially in dialogue systems.
Simcse: Simple contrastive learning of sentence embeddings
Tianyu Gao, Xingcheng Yao, and Danqi Chen. 2021 · 2021
Earlier work this paper cites.
Training a helpful and harmless assistant with reinforcement learning from human feedback
Yuntao Bai, Andy Jones, Kamal Ndousse, Amanda Askell, Anna Chen, Nova DasSarma, Dawn Drain, Stanislav Fort, Deep Ganguli, Tom Henighan, et al. 2022 · 2022
Earlier work this paper cites.
Toxigen: A large-scale machine-generated dataset for adversarial and implicit hate speech detection
Thomas Hartvigsen, Saadia Gabriel, Hamid Palangi, Maarten Sap, Dipankar Ray, and Ece Kamar. 2022 · 2022
Earlier work this paper cites.
A new generation of perspective api: Efficient multilingual character-level transformers
Alyssa Lees, Vinh Q. Tran, Yi Tay, Jeffrey Sorensen, Jai Gupta, Donald Metzler, and Lucy Vasserman. 2022 · 2022
Earlier work this paper cites.
Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022 · 2022
Earlier work this paper cites.
Red-teaming large language models using chain of utterances for safety-alignment
Rishabh Bhardwaj and Soujanya Poria. 2023 · 2023
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Chatgpt evaluation on sentence level relations: A focus on temporal, causal, and discourse relations
Chunkit Chan, Jiayang Cheng, Weiqi Wang, Yuxin Jiang, Tianqing Fang, Xin Liu, and Yangqiu Song. 2023 · 2023
Earlier work this paper cites.
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
Earlier work this paper cites.
Jailbreaker: Automated jailbreak across multiple large language model chatbots
Gelei Deng, Yi Liu, Yuekang Li, Kailong Wang, Ying Zhang, Zefeng Li, Haoyu Wang, Tianwei Zhang, and Yang Liu. 2023 · 2023
Earlier work this paper cites.
Large language models can be used to effectively scale spear phishing campaigns
Julian Hazell. 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. 2023 · 2023
Earlier work this paper cites.
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 · 2023
Cited alongside, same era.
Pretraining language models with human preferences
Tomasz Korbak, Kejian Shi, Angelica Chen, Rasika Vinayak Bhalerao, Christopher Buckley, Jason Phang, Samuel R Bowman, and Ethan Perez. 2023 · 2023
Cited alongside, same era.
Open sesame! universal black box jailbreaking of large language models
Raz Lapid, Ron Langberg, and Moshe Sipper. 2023 · 2023
Cited alongside, same era.
Rlaif: Scaling reinforcement learning from human feedback with ai feedback
Harrison Lee, Samrat Phatale, Hassan Mansoor, Kellie Lu, Thomas Mesnard, Colton Bishop, Victor Carbune, and Abhinav Rastogi. 2023 · 2023
Cited alongside, same era.
In-context impersonation reveals large language models’ strengths and biases
Leonard Salewski, Stephan Alaniz, Isabel Rio-Torto, Eric Schulz, and Zeynep Akata. 2023 · 2023
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Muhammad Ahmed Shah, Roshan Sharma, Hira Dhamyal, Raphael Olivier, Ankit Shah, Dareen Alharthi, Hazim T Bukhari, Massa Baali, Soham Deshmukh, Michael Kuhlmann, et al. 2023 · 2023
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Vishesh Thakur. 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, Aurelien Rodriguez, Robert Stojnic, Sergey Edunov, and Thomas Scialom. 2023 · 2023
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Haoran Li, Dadi Guo, Wei Fan, Mingshi Xu, and Yangqiu Song. 2023 · 2023
Cited alongside, same era.
Toxicchat: Unveiling hidden challenges of toxicity detection in real-world user-ai conversation
Zi Lin, Zihan Wang, Yongqi Tong, Yangkun Wang, Yuxin Guo, Yujia Wang, and Jingbo Shang. 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.
Tree of attacks: Jailbreaking black-box llms automatically
Anay Mehrotra, Manolis Zampetakis, Paul Kassianik, Blaine Nelson, Hyrum Anderson, Yaron Singer, and Amin Karbasi. 2023 · 2023
Cited alongside, same era.
A comprehensive overview of large language models
Humza Naveed, Asad Ullah Khan, Shi Qiu, Muhammad Saqib, Saeed Anwar, Muhammad Usman, Nick Barnes, and Ajmal Mian. 2023 · 2023
Cited alongside, same era.
OpenAI. 2023 · 2023
Cited alongside, same era.
Understanding multi-turn toxic behaviors in open-domain chatbots
Bocheng Chen, Guangjing Wang, Hanqing Guo, Yuanda Wang, and Qiben Yan. 2023a
Cited in the paper.
Learning to teach large language models logical reasoning
Meiqi Chen, Yubo Ma, Kaitao Song, Yixin Cao, Yan Zhang, and Dongsheng Li. 2023b
Cited in the paper.
Later among the works it cites.
The silence of the llms: Cross-lingual analysis of political bias and false information prevalence in chatgpt, google bard, and bing chat
Aleksandra Urman and Mykola Makhortykh. 2023 · 2023
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Using gpt-4 for content moderation
Lilian Weng, Vik Goel, and Andrea Vallone. 2023 · 2023
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Gptfuzzer: Red teaming large language models with auto-generated jailbreak prompts
Jiahao Yu, Xingwei Lin, and Xinyu Xing. 2023 · 2023
Later among the works it cites.
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. P Xing, Hao Zhang, Joseph E. Gonzalez, and Ion Stoica. 2023 · 2023
Later among the works it cites.
Autodan: Automatic and interpretable 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. 2023 · 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 · 2023
Later among the works it cites.