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The advent of large language models (LLMs) has revolutionized natural language processing, enabling the generation of coherent and contextually relevant human-like text.
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Lingua franca of personality: Taxonomies and structures based on the psycholexical approach
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The Big Five trait taxonomy: History, measurement, and theoretical perspectives
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Linguistic styles: Language use as an individual difference
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Common method biases in behavioral research: A critical review of the literature and recommended remedies
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Psychometric properties of the HEXACO Personality Inventory
Kibeom Lee and Michael C. Ashton · 2004
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Universal features of personality traits from the observer’s perspective: Data from 50 cultures
Robert R McCrae and Antonio Terracciano · 2005
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Daniel Nettle · 2006
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The power of personality: The comparative validity of personality traits, socioeconomic status, and cognitive ability for predicting important life outcomes
Brent W. Roberts, Nathan R. Kuncel, Rebecca Shiner, Avshalom Caspi, and Lewis R. Goldberg · 2007
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Paradigm shift to the integrative Big Five trait taxonomy: History, measurement, and conceptual issues
Oliver P. John, Laura P. Naumann, and Christopher J. Soto · 2008
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User–robot personality matching and assistive robot behavior adaptation for post-stroke rehabilitation therapy
Adriana Tapus, Cristian Ţăpuş, and Maja J Matarić · 2008
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Personality: The universal and the culturally specific
Steven J. Heine and Emma E. Buchtel · 2009
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Toward a theory of the Big Five
Colin G. DeYoung · 2010
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Testing predictions from personality neuroscience: Brain structure and the Big Five
Colin G DeYoung, Jacob B Hirsh, Matthew S Shane, Xenophon Papademetris, Nallakkandi Rajeevan, and Jeremy R Gray · 2010
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Linking “big” personality traits to anxiety, depressive, and substance use disorders: A meta-analysis
Roman Kotov, Wakiza Gamez, Frank Schmidt, and David Watson · 2010
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Measuring personality in wave I of the national longitudinal study of adolescent health
J Kenneth Young, Beaujean, and A Alexander · 2011
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Big Five personality traits as the predictors of creative self-efficacy and creative personal identity: Does gender matter?
Maciej Karwowski, Izabela Lebuda, Ewa Wisniewska, and Jacek Gralewski · 2013
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Private traits and attributes are predictable from digital records of human behavior
Michal Kosinski, David Stillwell, and Thore Graepel · 2013
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Personality, gender, and age in the language of social media: The open-vocabulary approach
H. Andrew Schwartz, Johannes C. Eichstaedt, Margaret L. Kern, Lukasz Dziurzynski, Stephanie M. Ramones, Megha Agrawal, Achal Shah, Michal Kosinski, David Stillwell, Martin E. P. Seligman, and Lyle H. Ungar · 2013
Cited alongside, same era.
Standards for educational and psychological testing
American Educational Research Association, American Psychological Association, and National Council on Measurement in Education, editors · 2014
Cited alongside, same era.
Standards for Educational and Psychological Testing
American Educational Research Association, American Psychological Association, National Council on Measurement in Education, Joint Committee on Standards for Educational, and Psychological Testing · 2014
Cited alongside, same era.
Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio · 2015
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Motivational basis of personality traits: A meta-analysis of value-personality correlations
Ronald Fischer and Diana Boer · 2015
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TruthfulQA: Measuring how models mimic human falsehoods
Stephanie Lin, Jacob Hilton, and Owain Evans · 2022
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Perfect: Prompt-free and efficient few-shot learning with language models
Rabeeh Karimi Mahabadi, Luke Zettlemoyer, James Henderson, Marzieh Saeidi, Lambert Mathias, Veselin Stoyanov, and Majid Yazdani · 2022
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Rethinking the role of demonstrations: What makes in-context learning work?
Sewon Min, Xinxi Lyu, Ari Holtzman, Mikel Artetxe, Mike Lewis, Hannaneh Hajishirzi, and Luke Zettlemoyer · 2022
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Who is GPT-3? an exploration of personality, values and demographics
Marilù Miotto, Nicola Rossberg, and Bennett Kleinberg · 2022
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ChatGPT, 2022
OpenAI · 2022
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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Facebook as a research tool for the social sciences: Opportunities, challenges, ethical considerations, and practical guidelines
Michal Kosinski, Sandra C Matz, Samuel D Gosling, Vesselin Popov, and David Stillwell · 2015
Cited alongside, same era.
Automatic personality assessment through social media language
Gregory Park, H Andrew Schwartz, Johannes C Eichstaedt, Margaret L Kern, Michal Kosinski, David J Stillwell, Lyle H Ungar, and Martin EP Seligman · 2015
Cited alongside, same era.
Personality traits and personal values: A meta-analysis
Laura Parks-Leduc, Gilad Feldman, and Anat Bardi · 2015
Cited alongside, same era.
Computer-based personality judgments are more accurate than those made by humans
Wu Youyou, Michal Kosinski, and David Stillwell · 2015
Cited alongside, same era.
The LAMBADA dataset: Word prediction requiring a broad discourse context
Denis Paperno, Germán Kruszewski, Angeliki Lazaridou, Ngoc Quan Pham, Raffaella Bernardi, Sandro Pezzelle, Marco Baroni, Gemma Boleda, and Raquel Fernández · 2016
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Language-based personality: A new approach to personality in a digital world
Ryan L Boyd and James W Pennebaker · 2017
Cited alongside, same era.
Psychological framing as an effective approach to real-life persuasive communication
Sandra Matz, Michal Kosinski, David Stillwell, and Gideon Nave · 2017
Cited alongside, same era.
Training language models to follow instructions with human feedback
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. 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 Christiano, Jan Leike, and Ryan Lowe · 2022
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Large language models open up new opportunities and challenges for psychometric assessment of artificial intelligence
Max Pellert, Clemens M Lechner, Claudia Wagner, Beatrice Rammstedt, and Markus Strohmaier · 2022
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Personality psychology
Brent W. Roberts and Hee J. Yoon · 2022
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Large pre-trained language models contain human-like biases of what is right and wrong to do
Patrick Schramowski, Cigdem Turan, Nico Andersen, Constantin A Rothkopf, and Kristian Kersting · 2022
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Kurt Shuster, Mojtaba Komeili, Leonard Adolphs, Stephen Roller, Arthur Szlam, and Jason Weston · 2022
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Language models can generate human-like self-reports of emotion
Mikke Tavast, Anton Kunnari, and Perttu Hämäläinen · 2022
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Trojan horse or useful helper? a relationship perspective on artificial intelligence assistants with humanlike features
Ertugrul Uysal, Sascha Alavi, and Valéry Bezençon · 2022
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Finetuned language models are zero-shot learners
Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, and Quoc V. Le · 2022
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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, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, and William Fedus · 2022
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Taxonomy of risks posed by language models
Laura Weidinger, Jonathan Uesato, Maribeth Rauh, Conor Griffin, Po-Sen Huang, John Mellor, Amelia Glaese, Myra Cheng, Borja Balle, Atoosa Kasirzadeh, Courtney Biles, Sasha Brown, Zac Kenton, Will Hawkins, Tom Stepleton, Abeba Birhane, Lisa Anne Hendricks, Laura Rimell, William Isaac, Julia Haas, Sean Legassick, Geoffrey Irving, and Iason Gabriel · 2022
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Thilo Hagendorff · 2023
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Can large language models truly understand prompts? a case study with negated prompts
Joel Jang, Seonghyeon Ye, and Minjoon Seo · 2023
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Mistral 7b
Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed · 2023
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Evaluating and inducing personality in pre-trained language models
Guangyuan Jiang, Manjie Xu, Song-Chun Zhu, Wenjuan Han, Chi Zhang, and Yixin Zhu · 2023
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Hang Jiang, Xiajie Zhang, Xubo Cao, and Jad Kabbara · 2023
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Estimating the personality of white-box language models
Saketh Reddy Karra, Son The Nguyen, and Theja Tulabandhula · 2023
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Efficient memory management for large language model serving with PagedAttention
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph E. Gonzalez, Hao Zhang, and Ion Stoica · 2023
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Xingxuan Li, Yutong Li, Shafiq Joty, Linlin Liu, Fei Huang, Lin Qiu, and Lidong Bing · 2023
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Lost in the middle: How language models use long contexts
Nelson F. Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang · 2023
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Dissociating language and thought in large language models: A cognitive perspective
Kyle Mahowald, Anna A Ivanova, Idan A Blank, Nancy Kanwisher, Joshua B Tenenbaum, and Evelina Fedorenko · 2023
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The debate over understanding in AI’s large language models
Melanie Mitchell and David C. Krakauer · 2023
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Auditing large language models: A three-layered approach
Jakob Mökander, Jonas Schuett, Hannah Rose Kirk, and Luciano Floridi · 2023
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OpenAI · 2023
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Do llms possess a personality? making the mbti test an amazing evaluation for large language models, 2023
Keyu Pan and Yawen Zeng · 2023
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The NLP task effectiveness of long-range transformers
Guanghui Qin, Yukun Feng, and Benjamin Van Durme · 2023
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Can AI have a personality?
Umarpreet Singh and Parham Aarabhi · 2023
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Xiaoyang Song, Akshat Gupta, Kiyan Mohebbizadeh, Shujie Hu, and Anant Singh · 2023
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The science of detecting LLM-generated texts
Ruixiang Tang, Yu-Neng Chuang, and Xia Hu · 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, Aurelien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample · 2023
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Large language models fail on trivial alterations to theory-of-mind tasks
Tomer Ullman · 2023
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Larger language models do in-context learning differently
Jerry Wei, Jason Wei, Yi Tay, Dustin Tran, Albert Webson, Yifeng Lu, Xinyun Chen, Hanxiao Liu, Da Huang, Denny Zhou, and Tengyu Ma · 2023
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Efficient guided generation for llms
Brandon T Willard and Rémi Louf · 2023
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A comprehensive study on post-training quantization for large language models
Zhewei Yao, Cheng Li, Xiaoxia Wu, Stephen Youn, and Yuxiong He · 2023
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Why Johnny can’t prompt: How non-AI experts try (and fail) to design LLM prompts
J.D. Zamfirescu-Pereira, Richmond Y. Wong, Bjoern Hartmann, and Qian Yang · 2023
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A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, Yifan Du, Chen Yang, Yushuo Chen, Zhipeng Chen, Jinhao Jiang, Ruiyang Ren, Yifan Li, Xinyu Tang, Zikang Liu, Peiyu Liu, Jian-Yun Nie, and Ji-Rong Wen · 2023
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Open llm leaderboard v2
Clémentine Fourrier, Nathan Habib, Alina Lozovskaya, Konrad Szafer, and Thomas Wolf · 2024
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Mixtral of experts, 2024
Albert Q. Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Lélio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Sandeep Subramanian, Sophia Yang, Szymon Antoniak, Teven Le Scao, Théophile Gervet, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed · 2024
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GPT-4o mini: advancing cost-efficient intelligence, 2024
OpenAI · 2024
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Incharacter: Evaluating personality fidelity in role-playing agents through psychological interviews
Xintao Wang, Yunze Xiao, Jen tse Huang, Siyu Yuan, Rui Xu, Haoran Guo, Quan Tu, Yaying Fei, Ziang Leng, Wei Wang, Jiangjie Chen, Cheng Li, and Yanghua Xiao · 2024
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