% Use this file for citations not found in the ACL Anthology (contained in "anthology.bib").

@misc{ryan2024unintendedimpactsllmalignment,
      title={Unintended Impacts of LLM Alignment on Global Representation}, 
      author={Michael J. Ryan and William Held and Diyi Yang},
      year={2024},
      eprint={2402.15018},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2402.15018}, 
}
 
@misc{wei2023jailbrokendoesllmsafety,
      title={Jailbroken: How Does LLM Safety Training Fail?}, 
      author={Alexander Wei and Nika Haghtalab and Jacob Steinhardt},
      year={2023},
      eprint={2307.02483},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2307.02483}, 
}

@misc{benkler2023assessingllmsmoralvalue,
      title={Assessing LLMs for Moral Value Pluralism}, 
      author={Noam Benkler and Drisana Mosaphir and Scott Friedman and Andrew Smart and Sonja Schmer-Galunder},
      year={2023},
      eprint={2312.10075},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2312.10075}, 
}

@misc{durmus2024measuringrepresentationsubjectiveglobal,
      title={Towards Measuring the Representation of Subjective Global Opinions in Language Models}, 
      author={Esin Durmus and Karina Nguyen and Thomas I. Liao and Nicholas Schiefer and Amanda Askell and Anton Bakhtin and Carol Chen and Zac Hatfield-Dodds and Danny Hernandez and Nicholas Joseph and Liane Lovitt and Sam McCandlish and Orowa Sikder and Alex Tamkin and Janel Thamkul and Jared Kaplan and Jack Clark and Deep Ganguli},
      year={2024},
      eprint={2306.16388},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2306.16388}, 
}
@misc{inan2023llamaguardllmbasedinputoutput,
      title={Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations}, 
      author={Hakan Inan and Kartikeya Upasani and Jianfeng Chi and Rashi Rungta and Krithika Iyer and Yuning Mao and Michael Tontchev and Qing Hu and Brian Fuller and Davide Testuggine and Madian Khabsa},
      year={2023},
      eprint={2312.06674},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2312.06674}, 
}
@misc{grattafiori2024llama3herdmodels,
      title={The Llama 3 Herd of Models}, 
      author={Aaron Grattafiori et al},
      year={2024},
      eprint={2407.21783},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2407.21783}, 
}
@misc{foo2024lionguardbuildingcontextualizedmoderation,
      title={LionGuard: Building a Contextualized Moderation Classifier to Tackle Localized Unsafe Content}, 
      author={Jessica Foo and Shaun Khoo},
      year={2024},
      eprint={2407.10995},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2407.10995}, 
}

@misc{bai2022constitutionalaiharmlessnessai,
      title={Constitutional AI: Harmlessness from AI Feedback}, 
      author={Yuntao Bai and Saurav Kadavath and Sandipan Kundu and Amanda Askell and Jackson Kernion and Andy Jones and Anna Chen and Anna Goldie and Azalia Mirhoseini and Cameron McKinnon and Carol Chen and Catherine Olsson and Christopher Olah and Danny Hernandez and Dawn Drain and Deep Ganguli and Dustin Li and Eli Tran-Johnson and Ethan Perez and Jamie Kerr and Jared Mueller and Jeffrey Ladish and Joshua Landau and Kamal Ndousse and Kamile Lukosuite and Liane Lovitt and Michael Sellitto and Nelson Elhage and Nicholas Schiefer and Noemi Mercado and Nova DasSarma and Robert Lasenby and Robin Larson and Sam Ringer and Scott Johnston and Shauna Kravec and Sheer El Showk and Stanislav Fort and Tamera Lanham and Timothy Telleen-Lawton and Tom Conerly and Tom Henighan and Tristan Hume and Samuel R. Bowman and Zac Hatfield-Dodds and Ben Mann and Dario Amodei and Nicholas Joseph and Sam McCandlish and Tom Brown and Jared Kaplan},
      year={2022},
      eprint={2212.08073},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2212.08073}, 
}

@misc{xu2024magpiealignmentdatasynthesis,
      title={Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing}, 
      author={Zhangchen Xu and Fengqing Jiang and Luyao Niu and Yuntian Deng and Radha Poovendran and Yejin Choi and Bill Yuchen Lin},
      year={2024},
      eprint={2406.08464},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2406.08464}, 
}
@misc{azar2023generaltheoreticalparadigmunderstand,
      title={A General Theoretical Paradigm to Understand Learning from Human Preferences}, 
      author={Mohammad Gheshlaghi Azar and Mark Rowland and Bilal Piot and Daniel Guo and Daniele Calandriello and Michal Valko and Rémi Munos},
      year={2023},
      eprint={2310.12036},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2310.12036}, 
}
@misc{yin2024relativepreferenceoptimizationenhancing,
      title={Relative Preference Optimization: Enhancing LLM Alignment through Contrasting Responses across Identical and Diverse Prompts}, 
      author={Yueqin Yin and Zhendong Wang and Yi Gu and Hai Huang and Weizhu Chen and Mingyuan Zhou},
      year={2024},
      eprint={2402.10958},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2402.10958}, 
}

@misc{xu2024contrastivepreferenceoptimizationpushing,
      title={Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation}, 
      author={Haoran Xu and Amr Sharaf and Yunmo Chen and Weiting Tan and Lingfeng Shen and Benjamin Van Durme and Kenton Murray and Young Jin Kim},
      year={2024},
      eprint={2401.08417},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2401.08417}, 
}
@misc{ethayarajh2024ktomodelalignmentprospect,
      title={KTO: Model Alignment as Prospect Theoretic Optimization}, 
      author={Kawin Ethayarajh and Winnie Xu and Niklas Muennighoff and Dan Jurafsky and Douwe Kiela},
      year={2024},
      eprint={2402.01306},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2402.01306}, 
}



@misc{geminiteam2024geminifamilyhighlycapable,
      title={Gemini: A Family of Highly Capable Multimodal Models}, 
      author={Gemini Team},
      year={2024},
      eprint={2312.11805},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2312.11805}, 
}

@misc{openai2024gpt4technicalreport,
      title={GPT-4 Technical Report}, 
      author={OpenAI},
      year={2024},
      eprint={2303.08774},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2303.08774}, 
}
@misc{openai2023gpt4card,
    title={GPT-4 System Card},
    author={OpenAI},
    year={2023},
    url={https://cdn.openai.com/papers/gpt-4-system-card.pdf}
}

@misc{rafailov2024directpreferenceoptimizationlanguage,
      title={Direct Preference Optimization: Your Language Model is Secretly a Reward Model}, 
      author={Rafael Rafailov and Archit Sharma and Eric Mitchell and Stefano Ermon and Christopher D. Manning and Chelsea Finn},
      year={2024},
      eprint={2305.18290},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2305.18290}, 
}
@misc{ziegler2020finetuninglanguagemodelshuman,
      title={Fine-Tuning Language Models from Human Preferences}, 
      author={Daniel M. Ziegler and Nisan Stiennon and Jeffrey Wu and Tom B. Brown and Alec Radford and Dario Amodei and Paul Christiano and Geoffrey Irving},
      year={2020},
      eprint={1909.08593},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/1909.08593}, 
}

@misc{xu2024dposuperiorppollm,
      title={Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study}, 
      author={Shusheng Xu and Wei Fu and Jiaxuan Gao and Wenjie Ye and Weilin Liu and Zhiyu Mei and Guangju Wang and Chao Yu and Yi Wu},
      year={2024},
      eprint={2404.10719},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2404.10719}, 
}

@misc{pang2024iterativereasoningpreferenceoptimization,
      title={Iterative Reasoning Preference Optimization}, 
      author={Richard Yuanzhe Pang and Weizhe Yuan and Kyunghyun Cho and He He and Sainbayar Sukhbaatar and Jason Weston},
      year={2024},
      eprint={2404.19733},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2404.19733}, 
}

@misc{thoppilan2022lamdalanguagemodelsdialog,
      title={LaMDA: Language Models for Dialog Applications}, 
      author={Romal Thoppilan and Daniel De Freitas and Jamie Hall and Noam Shazeer and Apoorv Kulshreshtha and Heng-Tze Cheng and Alicia Jin and Taylor Bos and Leslie Baker and Yu Du and YaGuang Li and Hongrae Lee and Huaixiu Steven Zheng and Amin Ghafouri and Marcelo Menegali and Yanping Huang and Maxim Krikun and Dmitry Lepikhin and James Qin and Dehao Chen and Yuanzhong Xu and Zhifeng Chen and Adam Roberts and Maarten Bosma and Vincent Zhao and Yanqi Zhou and Chung-Ching Chang and Igor Krivokon and Will Rusch and Marc Pickett and Pranesh Srinivasan and Laichee Man and Kathleen Meier-Hellstern and Meredith Ringel Morris and Tulsee Doshi and Renelito Delos Santos and Toju Duke and Johnny Soraker and Ben Zevenbergen and Vinodkumar Prabhakaran and Mark Diaz and Ben Hutchinson and Kristen Olson and Alejandra Molina and Erin Hoffman-John and Josh Lee and Lora Aroyo and Ravi Rajakumar and Alena Butryna and Matthew Lamm and Viktoriya Kuzmina and Joe Fenton and Aaron Cohen and Rachel Bernstein and Ray Kurzweil and Blaise Aguera-Arcas and Claire Cui and Marian Croak and Ed Chi and Quoc Le},
      year={2022},
      eprint={2201.08239},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2201.08239}, 
}

@misc{bai2022traininghelpfulharmlessassistant,
      title={Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback}, 
      author={Yuntao Bai and Andy Jones and Kamal Ndousse and Amanda Askell and Anna Chen and Nova DasSarma and Dawn Drain and Stanislav Fort and Deep Ganguli and Tom Henighan and Nicholas Joseph and Saurav Kadavath and Jackson Kernion and Tom Conerly and Sheer El-Showk and Nelson Elhage and Zac Hatfield-Dodds and Danny Hernandez and Tristan Hume and Scott Johnston and Shauna Kravec and Liane Lovitt and Neel Nanda and Catherine Olsson and Dario Amodei and Tom Brown and Jack Clark and Sam McCandlish and Chris Olah and Ben Mann and Jared Kaplan},
      year={2022},
      eprint={2204.05862},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2204.05862}, 
}
@article{Ningsih_Rahman_2023, title={Exploring the Unique Morphological and Syntactic Features of Singlish (Singapore English)}, volume={9}, url={https://publikasi.polije.ac.id/jeapco/article/view/3933}, DOI={10.25047/jeapco.v9i2.3933}, abstractNote={&amp;lt;p&amp;gt;Singapore is home to a number of significant ethnic groups, including Chinese, Malay, and Tamil, whose contributions have shaped the distinctive characteristics of Singlish in comparison to standard English. This study aims to examine the morphological and syntactic characteristics of Singlish, an English-based creole spoken in Singapore, emphasizing its impact on interethnic communication. Using comparative analysis, Singlish’s morphological and syntactic characteristics were compared to those of standard English and the languages of the three largest ethnic groups in Singapore (Chinese, Malay, and Tamil). Examining grammatical patterns, word order, sentence structure, and the use of particular linguistic features would be required. The findings demonstrate that Singlish utilizes distinctive syntactic patterns that frequently incorporate Malay, Chinese, and Tamil grammatical formulas. Singlish, in contrast to standard English, lacks subject and object pronouns and frequently employs &amp;quot;sentence-ending particles&amp;quot; such as &amp;lt;em&amp;gt;what, leh, lor, hah, &amp;lt;/em&amp;gt;and&amp;lt;em&amp;gt; meh&amp;lt;/em&amp;gt;, in addition to &amp;lt;em&amp;gt;lah&amp;lt;/em&amp;gt;. In addition, the copula be is frequently omitted before adjectives, nouns, and locatives in Singlish. In addition, the presence of word repetition and word drop in Singlish can be traced back to the Chinese dialect Hokkien. The Singaporean government has attempted to discourage the use of Singlish; however, this has sparked controversy due to the significance of the language in interethnic communication and its reflection of interethnic identity. As a result, Singlish is a fascinating subject for linguistic and sociological study, with significant implications for language education and policy.&amp;lt;/p&amp;gt;}, number={2}, journal={Journal of English in Academic and Professional Communication}, author={Ningsih, Nourma Silvia and Rahman, Fadhlur}, year={2023}, month={Jul.}, pages={72–80} }
@misc{yong2024lowresourcelanguagesjailbreakgpt4,
      title={Low-Resource Languages Jailbreak GPT-4}, 
      author={Zheng-Xin Yong and Cristina Menghini and Stephen H. Bach},
      year={2024},
      eprint={2310.02446},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2310.02446}, 
}

@misc{shen2024languagebarrierdissectingsafety,
      title={The Language Barrier: Dissecting Safety Challenges of LLMs in Multilingual Contexts}, 
      author={Lingfeng Shen and Weiting Tan and Sihao Chen and Yunmo Chen and Jingyu Zhang and Haoran Xu and Boyuan Zheng and Philipp Koehn and Daniel Khashabi},
      year={2024},
      eprint={2401.13136},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2401.13136}, 
}
@misc{mehrotra2024treeattacksjailbreakingblackbox,
      title={Tree of Attacks: Jailbreaking Black-Box LLMs Automatically}, 
      author={Anay Mehrotra and Manolis Zampetakis and Paul Kassianik and Blaine Nelson and Hyrum Anderson and Yaron Singer and Amin Karbasi},
      year={2024},
      eprint={2312.02119},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2312.02119}, 
}
@misc{hartvigsen2022toxigenlargescalemachinegenerateddataset,
      title={ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection}, 
      author={Thomas Hartvigsen and Saadia Gabriel and Hamid Palangi and Maarten Sap and Dipankar Ray and Ece Kamar},
      year={2022},
      eprint={2203.09509},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2203.09509}, 
}
@misc{perez2022redteaminglanguagemodels,
      title={Red Teaming Language Models with Language Models}, 
      author={Ethan Perez and Saffron Huang and Francis Song and Trevor Cai and Roman Ring and John Aslanides and Amelia Glaese and Nat McAleese and Geoffrey Irving},
      year={2022},
      eprint={2202.03286},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2202.03286}, 
}

@misc{zou2023universaltransferableadversarialattacks,
      title={Universal and Transferable Adversarial Attacks on Aligned Language Models}, 
      author={Andy Zou and Zifan Wang and Nicholas Carlini and Milad Nasr and J. Zico Kolter and Matt Fredrikson},
      year={2023},
      eprint={2307.15043},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2307.15043}, 
}
@misc{zhou2024alignmentjailbreakworkexplain,
      title={How Alignment and Jailbreak Work: Explain LLM Safety through Intermediate Hidden States}, 
      author={Zhenhong Zhou and Haiyang Yu and Xinghua Zhang and Rongwu Xu and Fei Huang and Yongbin Li},
      year={2024},
      eprint={2406.05644},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2406.05644}, 
}
@misc{zhou2024emulateddisalignmentsafetyalignment,
      title={Emulated Disalignment: Safety Alignment for Large Language Models May Backfire!}, 
      author={Zhanhui Zhou and Jie Liu and Zhichen Dong and Jiaheng Liu and Chao Yang and Wanli Ouyang and Yu Qiao},
      year={2024},
      eprint={2402.12343},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2402.12343}, 
}
@misc{ouyang2022traininglanguagemodelsfollow,
      title={Training language models to follow instructions with human feedback}, 
      author={Long Ouyang and Jeff Wu and Xu Jiang and Diogo Almeida and Carroll L. Wainwright and Pamela Mishkin and Chong Zhang and Sandhini Agarwal and Katarina Slama and Alex Ray and John Schulman and Jacob Hilton and Fraser Kelton and Luke Miller and Maddie Simens and Amanda Askell and Peter Welinder and Paul Christiano and Jan Leike and Ryan Lowe},
      year={2022},
      eprint={2203.02155},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2203.02155}, 
}
@misc{peng2024navigatingsafetylandscapemeasuring,
      title={Navigating the Safety Landscape: Measuring Risks in Finetuning Large Language Models}, 
      author={ShengYun Peng and Pin-Yu Chen and Matthew Hull and Duen Horng Chau},
      year={2024},
      eprint={2405.17374},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2405.17374}, 
}
@misc{arditi2024refusallanguagemodelsmediated,
      title={Refusal in Language Models Is Mediated by a Single Direction}, 
      author={Andy Arditi and Oscar Obeso and Aaquib Syed and Daniel Paleka and Nina Panickssery and Wes Gurnee and Neel Nanda},
      year={2024},
      eprint={2406.11717},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2406.11717}, 
}
@article{btmodel1952,
 ISSN = {00063444, 14643510},
 URL = {http://www.jstor.org/stable/2334029},
 author = {Ralph Allan Bradley and Milton E. Terry},
 journal = {Biometrika},
 number = {3/4},
 pages = {324--345},
 publisher = {[Oxford University Press, Biometrika Trust]},
 title = {Rank Analysis of Incomplete Block Designs: I. The Method of Paired Comparisons},
 urldate = {2025-01-03},
 volume = {39},
 year = {1952}
}

@misc{hu2021loralowrankadaptationlarge,
      title={LoRA: Low-Rank Adaptation of Large Language Models}, 
      author={Edward J. Hu and Yelong Shen and Phillip Wallis and Zeyuan Allen-Zhu and Yuanzhi Li and Shean Wang and Lu Wang and Weizhu Chen},
      year={2021},
      eprint={2106.09685},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2106.09685}, 
}

@article{eec14168-5714-3ca8-b073-d038266f2734,
 ISSN = {00129682, 14680262},
 URL = {http://www.jstor.org/stable/1914185},
 abstract = {This paper presents a critique of expected utility theory as a descriptive model of decision making under risk, and develops an alternative model, called prospect theory. Choices among risky prospects exhibit several pervasive effects that are inconsistent with the basic tenets of utility theory. In particular, people underweight outcomes that are merely probable in comparison with outcomes that are obtained with certainty. This tendency, called the certainty effect, contributes to risk aversion in choices involving sure gains and to risk seeking in choices involving sure losses. In addition, people generally discard components that are shared by all prospects under consideration. This tendency, called the isolation effect, leads to inconsistent preferences when the same choice is presented in different forms. An alternative theory of choice is developed, in which value is assigned to gains and losses rather than to final assets and in which probabilities are replaced by decision weights. The value function is normally concave for gains, commonly convex for losses, and is generally steeper for losses than for gains. Decision weights are generally lower than the corresponding probabilities, except in the range of low probabilities. Overweighting of low probabilities may contribute to the attractiveness of both insurance and gambling.},
 author = {Daniel Kahneman and Amos Tversky},
 journal = {Econometrica},
 number = {2},
 pages = {263--291},
 publisher = {[Wiley, Econometric Society]},
 title = {Prospect Theory: An Analysis of Decision under Risk},
 urldate = {2025-03-14},
 volume = {47},
 year = {1979}
}
