% references.bib - Safety Lens: White-Box Behavioral Alignment Detection

% === Representation Engineering & Steering ===

@article{zou_2023_representation,
  author    = {Zou, Andy and Phan, Long and Chen, Sarah and Campbell, James and Guo, Phillip and Ren, Richard and Pan, Alexander and Yin, Xuwang and Mazeika, Mantas and Dombrowski, Ann-Kathrin and Goel, Shashwat and Li, Nathaniel and Byun, Michael J. and Wang, Zifan and Mallen, Alex and Basart, Steven and Koyber, Sanmi and Song, Dawn and Fredrikson, Matt and Kolter, J. Zico and Hendrycks, Dan},
  title     = {Representation Engineering: A Top-Down Approach to {AI} Transparency},
  journal   = {arXiv preprint arXiv:2310.01405},
  year      = {2023},
}

@article{turner_2023_activation,
  author    = {Turner, Alexander Matt and Thiergart, Lisa and Udell, David and Leech, Gavin and Mini, Ulisse and Pelrine, Monte},
  title     = {Activation Addition: Steering Language Models Without Optimization},
  journal   = {arXiv preprint arXiv:2308.10248},
  year      = {2023},
}

@article{li_2024_iti,
  author    = {Li, Kenneth and Patel, Oam and Vi{\'e}gas, Fernanda and Pfister, Hanspeter and Wattenberg, Martin},
  title     = {Inference-Time Intervention: Eliciting Truthful Answers from a Language Model},
  journal   = {Advances in Neural Information Processing Systems (NeurIPS)},
  year      = {2024},
  volume    = {36},
}

% === Mechanistic Interpretability ===

@article{elhage_2021_circuits,
  author    = {Elhage, Nelson and Nanda, Neel and Olsson, Catherine and Henighan, Tom and Joseph, Nicholas and Mann, Ben and Askell, Amanda and Bai, Yuntao and Chen, Anna and Conerly, Tom and DasSarma, Nova and Drain, Dawn and Ganguli, Deep and Goldber, Zac and Kaplan, Jared and others},
  title     = {A Mathematical Framework for Transformer Circuits},
  journal   = {Transformer Circuits Thread},
  year      = {2021},
  publisher = {Anthropic},
  url       = {https://transformer-circuits.pub/2021/framework/index.html},
}

@article{olah_2020_zoom,
  author    = {Olah, Chris and Cammarata, Nick and Schubert, Ludwig and Goh, Gabriel and Petrov, Michael and Carter, Shan},
  title     = {Zoom In: An Introduction to Circuits},
  journal   = {Distill},
  year      = {2020},
  doi       = {10.23915/distill.00024.001},
}

@article{nanda_2023_othello,
  author    = {Nanda, Neel and Lee, Andrew and Wattenberg, Martin},
  title     = {Emergent Linear Representations in World Models of Self-Supervised Sequence Models},
  journal   = {arXiv preprint arXiv:2309.00941},
  year      = {2023},
}

% === Probing & Linear Representations ===

@article{belinkov_2022_probing,
  author    = {Belinkov, Yonatan},
  title     = {Probing Classifiers: Promises, Shortcomings, and Advances},
  journal   = {Computational Linguistics},
  year      = {2022},
  volume    = {48},
  number    = {1},
  pages     = {207--219},
  doi       = {10.1162/coli_a_00422},
}

@article{park_2023_linear,
  author    = {Park, Kiho and Choe, Yo Joong and Veitch, Victor},
  title     = {The Linear Representation Hypothesis and the Geometry of Large Language Models},
  journal   = {arXiv preprint arXiv:2311.03658},
  year      = {2023},
}

@article{burns_2023_ccs,
  author    = {Burns, Collin and Ye, Haotian and Klein, Dan and Steinhardt, Jacob},
  title     = {Discovering Latent Knowledge in Language Models Without Supervision},
  journal   = {arXiv preprint arXiv:2212.03827},
  year      = {2023},
  note      = {Published at ICLR 2023},
}

% === LLM Safety & Alignment ===

@article{ouyang_2022_instructgpt,
  author    = {Ouyang, Long and Wu, Jeffrey and Jiang, Xu and Almeida, Diogo and Wainwright, Carroll and Mishkin, Pamela and Zhang, Chong and Agarwal, Sandhini and Slama, Katarina and Ray, Alex and others},
  title     = {Training Language Models to Follow Instructions with Human Feedback},
  journal   = {Advances in Neural Information Processing Systems (NeurIPS)},
  year      = {2022},
  volume    = {35},
}

@article{bai_2022_helpful,
  author    = {Bai, Yuntao and Jones, Andy and Ndousse, Kamal and Askell, Amanda and Chen, Anna and DasSarma, Nova and Drain, Dawn and Fort, Stanislav and Ganguli, Deep and Henighan, Tom and others},
  title     = {Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback},
  journal   = {arXiv preprint arXiv:2204.05862},
  year      = {2022},
}

@article{wang_2023_decodingtrust,
  author    = {Wang, Boxin and Chen, Weixin and Pei, Hengzhi and Xie, Chulin and Kang, Mintong and Zhang, Chenhui and Xu, Chejian and Xiong, Zidi and Dutta, Ritik and Schaeffer, Rylan and others},
  title     = {{DecodingTrust}: A Comprehensive Assessment of Trustworthiness in {GPT} Models},
  journal   = {Advances in Neural Information Processing Systems (NeurIPS)},
  year      = {2023},
  volume    = {36},
}

% === Sycophancy & Deception ===

@article{sharma_2023_sycophancy,
  author    = {Sharma, Mrinank and Tong, Meg and Korbak, Tomasz and Duvenaud, David and Askell, Amanda and Bowman, Samuel R. and Cheng, Newton and Durmus, Esin and Hatfield-Dodds, Zac and Johnston, Scott R. and others},
  title     = {Towards Understanding Sycophancy in Language Models},
  journal   = {arXiv preprint arXiv:2310.13548},
  year      = {2023},
}

@article{perez_2022_discovering,
  author    = {Perez, Ethan and Ringer, Sam and Luk{\"o}siut{\.e}, Kamil{\.e} and Nguyen, Karina and Chen, Edwin and Heiner, Scott and Pettit, Craig and Olsson, Catherine and Kundu, Sandipan and Kadavath, Saurav and others},
  title     = {Discovering Language Model Behaviors with Model-Written Evaluations},
  journal   = {arXiv preprint arXiv:2212.09251},
  year      = {2022},
}

@article{park_2024_deception,
  author    = {Park, Peter S. and Goldstein, Simon and O'Gara, Aidan and Chen, Michael and Hendrycks, Dan},
  title     = {{AI} Deception: A Survey of Examples, Risks, and Potential Solutions},
  journal   = {Patterns},
  year      = {2024},
  volume    = {5},
  number    = {1},
  pages     = {100988},
  doi       = {10.1016/j.patter.2024.100988},
}

@article{hubinger_2024_sleeper,
  author    = {Hubinger, Evan and Denison, Carson and Mu, Jesse and Lambert, Mike and Tong, Meg and MacDiarmid, Monte and Lanham, Tamera and Ziegler, Daniel M. and Maxwell, Tim and Cheng, Newton and others},
  title     = {Sleeper Agents: Training Deceptive {LLMs} that Persist Through Safety Training},
  journal   = {arXiv preprint arXiv:2401.05566},
  year      = {2024},
}

% === Frameworks & Tools ===

@misc{wolf_2020_transformers,
  author    = {Wolf, Thomas and Debut, Lysandre and Sanh, Victor and Chaumond, Julien and Delangue, Clement and Moi, Anthony and Cistac, Pierric and Rault, Tim and Louf, R{\'e}mi and Funtowicz, Morgan and others},
  title     = {Transformers: State-of-the-Art Natural Language Processing},
  booktitle = {Proceedings of EMNLP 2020: System Demonstrations},
  year      = {2020},
  pages     = {38--45},
  doi       = {10.18653/v1/2020.emnlp-demos.6},
}

@article{paszke_2019_pytorch,
  author    = {Paszke, Adam and Gross, Sam and Massa, Francisco and Lerer, Adam and Bradbury, James and Chanan, Gregory and Killeen, Trevor and Lin, Zeming and Gimelshein, Natalia and Antiga, Luca and others},
  title     = {{PyTorch}: An Imperative Style, High-Performance Deep Learning Library},
  journal   = {Advances in Neural Information Processing Systems (NeurIPS)},
  year      = {2019},
  volume    = {32},
}

@misc{fourrier_2024_lighteval,
  author    = {Fourrier, Cl{\'e}mentine and Habib, Nathan and Wolf, Thomas and Tunstall, Lewis},
  title     = {{LightEval}: A Lightweight Framework for {LLM} Evaluation},
  year      = {2024},
  howpublished = {\url{https://github.com/huggingface/lighteval}},
}

% === Foundation Models ===

@article{radford_2019_gpt2,
  author    = {Radford, Alec and Wu, Jeffrey and Child, Rewon and Luan, David and Amodei, Dario and Sutskever, Ilya},
  title     = {Language Models are Unsupervised Multitask Learners},
  journal   = {OpenAI Blog},
  year      = {2019},
}

@article{touvron_2023_llama,
  author    = {Touvron, Hugo and Martin, Louis and Stone, Kevin and Albert, Peter and Almahairi, Amjad and Babaei, Yasmine and Bashlykov, Nikolay and Batra, Soumya and Bhargava, Prajjwal and Bhosale, Shruti and others},
  title     = {{LLaMA} 2: Open Foundation and Fine-Tuned Chat Models},
  journal   = {arXiv preprint arXiv:2307.09288},
  year      = {2023},
}

@article{jiang_2023_mistral,
  author    = {Jiang, Albert Q. and Sablayrolles, Alexandre and Mensch, Arthur and Bamford, Chris and Chaplot, Devendra Singh and de las Casas, Diego and Bressand, Florian and Lengyel, Gianna and Lample, Guillaume and Saulnier, Lucile and others},
  title     = {Mistral {7B}},
  journal   = {arXiv preprint arXiv:2310.06825},
  year      = {2023},
}

@article{vaswani_2017_attention,
  author    = {Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and Uszkoreit, Jakob and Jones, Llion and Gomez, Aidan N. and Kaiser, {\L}ukasz and Polosukhin, Illia},
  title     = {Attention Is All You Need},
  journal   = {Advances in Neural Information Processing Systems (NeurIPS)},
  year      = {2017},
  volume    = {30},
}

% === Interpretability Methods ===

@article{conmy_2023_acdc,
  author    = {Conmy, Arthur and Mavor-Parker, Augustine N. and Lynch, Aengus and Heimersheim, Stefan and Garriga-Alonso, Adri{\`a}},
  title     = {Towards Automated Circuit Discovery for Mechanistic Interpretability},
  journal   = {Advances in Neural Information Processing Systems (NeurIPS)},
  year      = {2023},
  volume    = {36},
}

@article{marks_2024_geometry,
  author    = {Marks, Samuel and Tegmark, Max},
  title     = {The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets},
  journal   = {arXiv preprint arXiv:2310.06824},
  year      = {2024},
}
