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Inspiration is linked to various positive outcomes, such as increased creativity, productivity, and happiness.
Language models are few-shot learners
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Tin Kam Ho. 1995 · 1995
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Poetry and Prophecy: The Anthropology of Inspiration
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Approach-avoidance motivation in personality: approach and avoidance temperaments and goals
Andrew J Elliot and Todd M Thrash. 2002 · 2002
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Using tf-idf to determine word relevance in document queries
Juan Ramos et al. 2003 · 2003
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Inspiration as a psychological construct
Todd M. Thrash and Andrew J Elliot. 2003 · 2003
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Inspiration: core characteristics, component processes, antecedents, and function
Todd M. Thrash and Andrew J Elliot. 2004 · 2004
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Linguistic inquiry and word count (LIWC2007)
James W. Pennebaker, Roger John Booth, and Martha E. Francis. 2007 · 2007
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Revealing dimensions of thinking in open-ended self-descriptions: An automated meaning extraction method for natural language
Cindy K Chung and James W Pennebaker. 2008 · 2008
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Opinion mining and sentiment analysis
Bo Pang, Lillian Lee, et al. 2008 · 2008
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Mediating between the muse and the masses: inspiration and the actualization of creative ideas
Todd M. Thrash, Laura A. Maruskin, Scott E. Cassidy, James W. Fryer, and Richard M. Ryan. 2010 · 2010
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Scikit-learn: Machine learning in Python
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Inspired to get there: The effects of trait and goal inspiration on goal progress
Marina Milyavskaya, Iana Ianakieva, Emily Foxen-Craft, Agnes Colantuoni, and Richard Koestner. 2012 · 2012
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Choosing the right words: Characterizing and reducing error of the word count approach
H Andrew Schwartz, Johannes Eichstaedt, Eduardo Blanco, Lukasz Dziurzynski, Margaret Kern, Stephanie Ramones, Martin Seligman, and Lyle Ungar. 2013 · 2013
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The scientific study of inspiration in the creative process: challenges and opportunities
Victoria C. Oleynick, Todd M. Thrash, Michael C. LeFew, Emil G. Moldovan, and Paul D. Kieffaber. 2014 · 2014
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When small words foretell academic success: The case of college admissions essays
James W Pennebaker, Cindy K Chung, Joey Frazee, Gary M Lavergne, and David I Beaver. 2014 · 2014
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Performing multilingual analysis with linguistic inquiry and word count 2015 (liwc2015). an equivalence study of four languages
Diana Paula Dudău and Florin Alin Sava. 2021 · 2015
Detecting inspiring content on social media
Oana Ignat, Y-Lan Boureau, Jane A. Yu, and Alon Y. Halevy. 2021 · 2021
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Learning from the worst: Dynamically generated datasets to improve online hate detection
Bertie Vidgen, Tristan Thrush, Zeerak Waseem, and Douwe Kiela. 2021 · 2021
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Normsage: Multi-lingual multi-cultural norm discovery from conversations on-the-fly
Yi R Fung, Tuhin Chakraborty, Hao Guo, Owen Rambow, Smaranda Muresan, and Heng Ji. 2022 · 2022
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LoRA: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2022 · 2022
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Potato: The portable text annotation tool
Jiaxin Pei, Aparna Ananthasubramaniam, Xingyao Wang, Naitian Zhou, Apostolos Dedeloudis, Jackson Sargent, and David Jurgens. 2022 · 2022
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The development and psychometric properties of LIWC2015
James W. Pennebaker, Ryan L. Boyd, Kayla Jordan, and Kate G. Blackburn. 2015 · 2015
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Reassessing the facebook experiment: critical thinking about the validity of big data research
Galen Panger. 2016 · 2016
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Youtube for good: A content analysis and examination of elicitors of self-transcendent media
Katherine R Dale, Arthur A Raney, Sophie H Janicke, Meghan S Sanders, and Mary Beth Oliver. 2017 · 2017
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Scattertext: a browser-based tool for visualizing how corpora differ
Jason Kessler. 2017 · 2017
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Profiling the audience for self-transcendent media: A national survey
Arthur A Raney, Sophie H Janicke, Mary Beth Oliver, Katherine R Dale, Robert P Jones, and Daniel Cox. 2018 · 2018
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Examining long-term trends in politics and culture through language of political leaders and cultural institutions
Kayla N Jordan, Joanna Sterling, James W Pennebaker, and Ryan L Boyd. 2019 · 2019
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The daily dose of digital inspiration: A multi-method exploration of meaningful communication in social media
Diana Rieger and Christoph Klimmt. 2019 · 2019
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Wordcraft: story writing with large language models
Ann Yuan, Andy Coenen, Emily Reif, and Daphne Ippolito. 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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Prompting a large language model to generate diverse motivational messages: A comparison with human-written messages
Samuel Rhys Cox, Ashraf Abdul, and Wei Tsang Ooi. 2023 · 2023
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When the majority is wrong: Modeling annotator disagreement for subjective tasks
Eve Fleisig, Rediet Abebe, and Dan Klein. 2023 · 2023
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Culturally aware natural language inference
Jing Huang and Diyi Yang. 2023 · 2023
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Human heuristics for ai-generated language are flawed
Maurice Jakesch, Jeffrey T Hancock, and Mor Naaman. 2023 · 2023
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Working with ai to persuade: Examining a large language model’s ability to generate pro-vaccination messages
Elise Karinshak, Sunny Xun Liu, Joon Sung Park, and Jeffrey T Hancock. 2023 · 2023
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Natural language generation for advertising: A survey
Soichiro Murakami, Sho Hoshino, and Peinan Zhang. 2023 · 2023
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Knowledge of cultural moral norms in large language models
Aida Ramezani and Yang Xu. 2023 · 2023
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The science of detecting llm-generated texts
Ruixiang Tang, Yu-Neng Chuang, and Xia Hu. 2023 · 2023
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A survey on llm-generated text detection: Necessity, methods, and future directions
Junchao Wu, Shu Yang, Runzhe Zhan, Yulin Yuan, Derek F. Wong, and Lidia S. Chao. 2023 · 2023
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