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Due to the widespread use of large language models (LLMs), we need to understand whether they embed a specific "worldview" and what these views reflect.
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Do llms exhibit human-like response biases? a case study in survey design
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Llama 2: Open foundation and fine-tuned chat models
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Large language models are not robust multiple choice selectors
Chujie Zheng, Hao Zhou, Fandong Meng, Jie Zhou, and Minlie Huang. 2023 · 2023
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Simple linguistic inferences of large language models (LLMs): Blind spots and blinds
Victoria Basmov, Yoav Goldberg, and Reut Tsarfaty. 2024 · 2024
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Navigating the modern evaluation landscape: Considerations in benchmarks and frameworks for large language models (LLMs)
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Scaling instruction-finetuned language models
Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Yunxuan Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, et al. 2024 · 2024
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Datasets for large language models: A comprehensive survey
Yang Liu, Jiahuan Cao, Chongyu Liu, Kai Ding, and Lianwen Jin. 2024 · 2024
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State of what art? a call for multi-prompt llm evaluation
Moran Mizrahi, Guy Kaplan, Dan Malkin, Rotem Dror, Dafna Shahaf, and Gabriel Stanovsky. 2024 · 2024
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More human than human: Measuring ChatGPT political bias
Fabio Motoki, Valdemar Pinho Neto, and Victor Rodrigues. 2024 · 2024
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The self-perception and political biases of chatgpt
Jérôme Rutinowski, Sven Franke, Jan Endendyk, Ina Dormuth, Moritz Roidl, and Markus Pauly. 2024 · 2024
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You don’t need a personality test to know these models are unreliable: Assessing the reliability of large language models on psychometric instruments
Bangzhao Shu, Lechen Zhang, Minje Choi, Lavinia Dunagan, Lajanugen Logeswaran, Moontae Lee, Dallas Card, and David Jurgens. 2024 · 2024
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Chatgpt usage in everyday life: A motivation-theoretic mixed-methods study
Vinzenz Wolf and Christian Maier. 2024 · 2024
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