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To ensure AI safety, instruction-tuned Large Language Models (LLMs) are specifically trained to ensure alignment, which refers to making models behave in accordance with human intentions.
Fine-grained analysis of sentence embeddings using auxiliary prediction tasks
Yossi Adi, Einat Kermany, Yonatan Belinkov, Ofer Lavi, and Yoav Goldberg. 2016 · 2016
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What do Neural Machine Translation Models Learn about Morphology?. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . Association for Computational Linguistics, Vancouver, Canada, 861–872
Yonatan Belinkov, Nadir Durrani, Fahim Dalvi, Hassan Sajjad, and James Glass. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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BERT rediscovers the classical NLP pipeline
Ian Tenney, Dipanjan Das, and Ellie Pavlick. 2019 · 2019
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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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StereoSet: Measuring stereotypical bias in pretrained language models
Moin Nadeem, Anna Bethke, and Siva Reddy. 2020 · 2020
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Autoprompt: Eliciting knowledge from language models with automatically generated prompts
Taylor Shin, Yasaman Razeghi, Robert L Logan IV, Eric Wallace, and Sameer Singh. 2020 · 2020
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Investigating gender bias in language models using causal mediation analysis
Jesse Vig, Sebastian Gehrmann, Yonatan Belinkov, Sharon Qian, Daniel Nevo, Yaron Singer, and Stuart Shieber. 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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Persistent anti-muslim bias in large language models. In Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society . 298–306
Abubakar Abid, Maheen Farooqi, and James Zou. 2021 · 2021
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Extracting training data from large language models. In 30th USENIX Security Symposium (USENIX Security 21) . 2633–2650
Nicholas Carlini, Florian Tramer, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song, Ulfar Erlingsson, et al · 2021
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Tag: Gradient attack on transformer-based language models
Jieren Deng, Yijue Wang, Ji Li, Chao Shang, Hang Liu, Sanguthevar Rajasekaran, and Caiwen Ding. 2021 · 2021
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Bold: Dataset and metrics for measuring biases in open-ended language generation. In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency . 862–872
Jwala Dhamala, Tony Sun, Varun Kumar, Satyapriya Krishna, Yada Pruksachatkun, Kai-Wei Chang, and Rahul Gupta. 2021 · 2021
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A mathematical framework for transformer circuits. Transformer Circuits Thread, 2021
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Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) . Association for Computational Linguistics, Online, 1828–1843
Matthew Finlayson, Aaron Mueller, Sebastian Gehrmann, Stuart Shieber, Tal Linzen, and Yonatan Belinkov. 2021 · 2021
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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. 2021 · 2021
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Truthfulqa: Measuring how models mimic human falsehoods
Stephanie Lin, Jacob Hilton, and Owain Evans. 2021 · 2021
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Recent advances in natural language processing via large pre-trained language models: A survey
Bonan Min, Hayley Ross, Elior Sulem, Amir Pouran Ben Veyseh, Thien Huu Nguyen, Oscar Sainz, Eneko Agirre, Ilana Heintz, and Dan Roth. 2021 · 2021
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Constitutional ai: Harmlessness from ai feedback
Yuntao Bai, Saurav Kadavath, Sandipan Kundu, Amanda Askell, Jackson Kernion, Andy Jones, Anna Chen, Anna Goldie, Azalia Mirhoseini, Cameron McKinnon, et al · 2022
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Probing Classifiers: Promises, Shortcomings, and Advances
Yonatan Belinkov. 2022 · 2022
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Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, et al · 2022
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Ppt: Backdoor attacks on pre-trained models via poisoned prompt tuning. In Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, IJCAI-22 . 680–686
Wei Du, Yichun Zhao, Boqun Li, Gongshen Liu, and Shilin Wang. 2022 · 2022
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Improving alignment of dialogue agents via targeted human judgements
Amelia Glaese, Nat McAleese, Maja Trębacz, John Aslanides, Vlad Firoiu, Timo Ewalds, Maribeth Rauh, Laura Weidinger, Martin Chadwick, Phoebe Thacker, et al · 2022
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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
Cited alongside, same era.
VADER-Sentiment-Analysis
C.J. Hutto. 2022 · 2022
Cited alongside, same era.
Emergent world representations: Exploring a sequence model trained on a synthetic task
Kenneth Li, Aspen K Hopkins, David Bau, Fernanda Viégas, Hanspeter Pfister, and Martin Wattenberg. 2022 · 2022
Cited alongside, same era.
Locating and editing factual associations in GPT
Kevin Meng, David Bau, Alex Andonian, and Yonatan Belinkov. 2022a · 2022
Cited alongside, same era.
Mass-editing memory in a transformer
Kevin Meng, Arnab Sen Sharma, Alex Andonian, Yonatan Belinkov, and David Bau. 2022b · 2022
Cited alongside, same era.
Survey of hallucination in natural language generation
Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Ye Jin Bang, Andrea Madotto, and Pascale Fung. 2023 · 2023
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Pretraining language models with human preferences. In International Conference on Machine Learning . PMLR, 17506–17533
Tomasz Korbak, Kejian Shi, Angelica Chen, Rasika Vinayak Bhalerao, Christopher Buckley, Jason Phang, Samuel R Bowman, and Ethan Perez. 2023 · 2023
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Multi-step jailbreaking privacy attacks on chatgpt
Haoran Li, Dadi Guo, Wei Fan, Mingshi Xu, and Yangqiu Song. 2023a · 2023
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Inference-Time Intervention: Eliciting Truthful Answers from a Language Model
Kenneth Li, Oam Patel, Fernanda Viégas, Hanspeter Pfister, and Martin Wattenberg. 2023b · 2023
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Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models’ Alignment
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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
Cited alongside, same era.
Training language models to follow instructions with human feedback. In Advances in Neural Information Processing Systems , S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, and A. Oh (Eds.), Vol. 35. Curran Associates, Inc., 27730–27744
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul F Christiano, Jan Leike, and Ryan Lowe. 2022b · 2022
Cited alongside, same era.
Ignore previous prompt: Attack techniques for language models
Fábio Perez and Ian Ribeiro. 2022 · 2022
Cited alongside, same era.
Extracting latent steering vectors from pretrained language models
Nishant Subramani, Nivedita Suresh, and Matthew E Peters. 2022 · 2022
Cited alongside, same era.
Self-instruct: Aligning language model with self generated instructions
Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A Smith, Daniel Khashabi, and Hannaneh Hajishirzi. 2022 · 2022
Cited alongside, same era.
Emergent abilities of large language models
Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, et al · 2022
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
Cited alongside, same era.
Yang Liu, Yuanshun Yao, Jean-Francois Ton, Xiaoying Zhang, Ruocheng Guo Hao Cheng, Yegor Klochkov, Muhammad Faaiz Taufiq, and Hang Li. 2023 · 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 · 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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Code llama: Open foundation models for code
Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, Sten Sootla, Itai Gat, Xiaoqing Ellen Tan, Yossi Adi, Jingyu Liu, Tal Remez, Jérémy Rapin, et al · 2023
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Xinyue Shen, Zeyuan Chen, Michael Backes, Yun Shen, and Yang Zhang. 2023 · 2023
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al · 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, et al · 2023
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Activation Addition: Steering Language Models Without Optimization
Alex Turner, Lisa Thiergart, David Udell, Gavin Leech, Ulisse Mini, and Monte MacDiarmid. 2023 · 2023
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Poisoning Language Models During Instruction Tuning
Alexander Wan, Eric Wallace, Sheng Shen, and Dan Klein. 2023 · 2023
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Aligning large language models with human: A survey
Yufei Wang, Wanjun Zhong, Liangyou Li, Fei Mi, Xingshan Zeng, Wenyong Huang, Lifeng Shang, Xin Jiang, and Qun Liu. 2023 · 2023
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Simple synthetic data reduces sycophancy in large language models
Jerry Wei, Da Huang, Yifeng Lu, Denny Zhou, and Quoc V Le. 2023 · 2023
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Bloomberggpt: A large language model for finance
Shijie Wu, Ozan Irsoy, Steven Lu, Vadim Dabravolski, Mark Dredze, Sebastian Gehrmann, Prabhanjan Kambadur, David Rosenberg, and Gideon Mann. 2023 · 2023
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Large language models can be good privacy protection learners
Yijia Xiao, Yiqiao Jin, Yushi Bai, Yue Wu, Xianjun Yang, Xiao Luo, Wenchao Yu, Xujiang Zhao, Yanchi Liu, Haifeng Chen, et al · 2023
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Synthetic Lies: Understanding AI-Generated Misinformation and Evaluating Algorithmic and Human Solutions. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (Hamburg, Germany) (CHI ’23) . Association for Computing Machinery, New York, NY, USA, Article 436, 20 pages
Jiawei Zhou, Yixuan Zhang, Qianni Luo, Andrea G Parker, and Munmun De Choudhury. 2023a · 2023
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Synthetic lies: Understanding ai-generated misinformation and evaluating algorithmic and human solutions. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems . 1–20
Jiawei Zhou, Yixuan Zhang, Qianni Luo, Andrea G Parker, and Munmun De Choudhury. 2023b · 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
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Trustllm: Trustworthiness in large language models
Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, et al · 2024
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Hard prompts made easy: Gradient-based discrete optimization for prompt tuning and discovery
Yuxin Wen, Neel Jain, John Kirchenbauer, Micah Goldblum, Jonas Geiping, and Tom Goldstein. 2024 · 2024
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