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Dual process theory posits that human cognition arises via two systems.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
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A new measure of rank correlation
M. G. Kendall. 1938 · 1938
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Stereoset: Measuring stereotypical bias in pretrained language models
Moin Nadeem, Anna Bethke, and Siva Reddy. 2020 · 2004
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How we know our own minds: The relationship between mindreading and metacognition
Peter Carruthers. 2009 · 2009
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Dual-process and dual-system theories of reasoning
Keith Frankish. 2010 · 2010
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Dual-process theories of higher cognition: Advancing the debate
Jonathan St BT Evans and Keith E Stanovich. 2013 · 2013
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Towards understanding and mitigating social biases in language models
Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency, and Ruslan Salakhutdinov. 2021 · 2021
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Self-diagnosis and self-debiasing: A proposal for reducing corpus-based bias in nlp
Timo Schick, Sahana Udupa, and Hinrich Schütze. 2021 · 2021
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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 · 2022
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023 · 2023
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Evaluating large language models with neubaroco: Syllogistic reasoning ability and human-like biases
Risako Ando, Takanobu Morishita, Hirohiko Abe, Koji Mineshima, and Mitsuhiro Okada. 2023 · 2023
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Dual process theory for large language models: An overview of using psychology to address hallucination and reliability issues
Samuel C Bellini-Leite. 2023 · 2023
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Fast and slow language processing: A window into dual-process models of cognition.[open peer commentary on de neys]
Fernanda Ferreira and Falk Huettig. 2023 · 2023
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Human-like intuitive behavior and reasoning biases emerged in large language models but disappeared in chatgpt
Thilo Hagendorff, Sarah Fabi, and Michal Kosinski. 2023 · 2023
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Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al. 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, et al. 2023 · 2023
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Towards understanding chain-of-thought prompting: An empirical study of what matters
Investigating subtler biases in LLMs: Ageism, beauty, institutional, and nationality bias in generative models
Mahammed Kamruzzaman, Md. Shovon, and Gene Kim. 2024b · 2024
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Evaluating gender bias in large language models via chain-of-thought prompting
Masahiro Kaneko, Danushka Bollegala, Naoaki Okazaki, and Timothy Baldwin. 2024 · 2024
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Lookalike: Human mimicry based collaborative decision making
Rabimba Karanjai and Weidong Shi. 2024 · 2024
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(ir) rationality and cognitive biases in large language models
Olivia Macmillan-Scott and Mirco Musolesi. 2024 · 2024
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An Inference-Centric Approach to Natural Language Processing and Cognitive Modeling
Animesh Nighojkar. 2024 · 2024
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Boshi Wang, Sewon Min, Xiang Deng, Jiaming Shen, You Wu, Luke Zettlemoyer, and Huan Sun. 2023 · 2023
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Towards better chain-of-thought prompting strategies: A survey
Zihan Yu, Liang He, Zhen Wu, Xinyu Dai, and Jiajun Chen. 2023 · 2023
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Counterfactual data augmentation for mitigating gender stereotypes in languages with rich morphology
Ran Zmigrod, Sabrina J Mielke, Hanna Wallach, and Ryan Cotterell. 2019 · 2023
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Helpful assistant or fruitful facilitator? investigating how personas affect language model behavior
Pedro Henrique Luz de Araujo and Benjamin Roth. 2024 · 2024
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Sensitivity, performance, robustness: Deconstructing the effect of sociodemographic prompting
Tilman Beck, Hendrik Schuff, Anne Lauscher, and Iryna Gurevych. 2024 · 2024
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Prompting fairness: Learning prompts for debiasing large language models
Andrei-Victor Chisca, Andrei-Cristian Rad, and Camelia Lemnaru. 2024 · 2024
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Axolotl: Fairness through assisted self-debiasing of large language model outputs
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Self-debiasing large language models: Zero-shot recognition and reduction of stereotypes
Isabel O Gallegos, Ryan A Rossi, Joe Barrow, Md Mehrab Tanjim, Tong Yu, Hanieh Deilamsalehy, Ruiyi Zhang, Sungchul Kim, and Franck Dernoncourt. 2024 · 2024
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A study on the representativeness heuristics problem in large language models
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Do large language models show decision heuristics similar to humans? a case study using gpt-3.5
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Gemma 2: Improving open language models at a practical size
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What evidence do language models find convincing?
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Pengda Wang, Zilin Xiao, Hanjie Chen, and Frederick L Oswald. 2024 · 2024
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Giving ai personalities leads to more human-like reasoning
Animesh Nighojkar, Bekhzodbek Moydinboyev, My Duong, and John Licato. 2025 · 2025
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