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Large Language Models (LLMs) demonstrate remarkable proficiency in generating accurate and fluent text.
An empirical investigation of the impact of chatgpt on creativity
B.C. Lee and J. Chung. 2024 · 1914
Earlier work this paper cites.
Mtld, vocd-d, and hd-d: A validation study of sophisticated approaches to lexical diversity assessment
P. M. McCarthy and S. Jarvis. 2010 · 2010
Earlier work this paper cites.
TAP-DLND 1.0 : A corpus for document level novelty detection
Tirthankar Ghosal, Amitra Salam, Swati Tiwary, Asif Ekbal, and Pushpak Bhattacharyya. 2018 · 2018
Earlier work this paper cites.
Texygen: A benchmarking platform for text generation models
Yaoming Zhu, Sidi Lu, Lei Zheng, Jiaxian Guo, Weinan Zhang, Jun Wang, and Yong Yu. 2018 · 2018
Earlier work this paper cites.
BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Earlier work this paper cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Earlier work this paper cites.
Novelty detection: A perspective from natural language processing
Tirthankar Ghosal, Tanik Saikh, Tameesh Biswas, Asif Ekbal, and Pushpak Bhattacharyya. 2022 · 2022
Earlier work this paper cites.
Experimental narratives: A comparison of human crowdsourced storytelling and AI storytelling
Nina Begus. 2023 · 2023
Earlier work this paper cites.
The originality of machines: Ai takes the torrance test
Erik E. Guzik, Christian Byrge, and Christian Gilde. 2023 · 2023
Earlier work this paper cites.
Wharton study pits chatgpt against mba students in creativity test
Matt Kefford. 2023 · 2023
Earlier work this paper cites.
Science fiction magazines battle a flood of chatbot-generated stories
Michael Levenson. 2023 · 2023
Earlier work this paper cites.
How much do language models copy from their training data? evaluating linguistic novelty in text generation using RAVEN
R. Thomas McCoy, Paul Smolensky, Tal Linzen, Jianfeng Gao, and Asli Celikyilmaz. 2023 · 2023
Cited alongside, same era.
OpenAI. 2023 · 2023
Cited alongside, same era.
Ai-generated fiction is flooding literary magazines — but not fooling anyone
Mia Sato. 2023 · 2023
Cited alongside, same era.
Art or artifice? large language models and the false promise of creativity
Tuhin Chakrabarty, Philippe Laban, Divyansh Agarwal, Smaranda Muresan, and Chien-Sheng Wu. 2024 · 2024
Cited alongside, same era.
DeepSeek-AI, Aixin Liu, Bei Feng, Bing Xue, Bingxuan Wang, Bochao Wu, Chengda Lu, Chenggang Zhao, Chengqi Deng, Chenyu Zhang, Chong Ruan, Damai Dai, Daya Guo, Dejian Yang, Deli Chen, Dongjie Ji, Erhang Li, Fangyun Lin, Fucong Dai, and 81 others. 2024 · 2024
The language of creativity: Evidence from humans and large language models
William Orwig, Emma Edenbaum, Joshua Greene, and Daniel Schacter. 2024 · 2024
Later among the works it cites.
Divergent creativity in humans and large language models
Antoine Bellemare Pépin, François Lespinasse, Philipp Thölke, Yann Harel, Kory Mathewson, Jay A. Olson, Yoshua Bengio, and Karim Jerbi. 2024 · 2024
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Ai-generated poetry is indistinguishable from human-written poetry and is rated more favorably
B. Porter and E. Machery. 2024 · 2024
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Standardizing the measurement of text diversity: A tool and a comparative analysis of scores
Chantal Shaib, Joe Barrow, Jiuding Sun, Alexa F. Siu, Byron C. Wallace, and Ani Nenkova. 2024 · 2024
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Can llms generate novel research ideas? a large-scale human study with 100+ nlp researchers
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Cited alongside, same era.
Generative ai enhances individual creativity but reduces the collective diversity of novel content
Anil R. Doshi and Oliver P. Hauser. 2024 · 2024
Cited alongside, same era.
The gpt-writingprompts dataset: A comparative analysis of character portrayal in short stories
Xi Yu Huang, Krishnapriya Vishnubhotla, and Frank Rudzicz. 2024 · 2024
Cited alongside, same era.
Delving into chatgpt usage in academic writing through excess vocabulary
Dmitry Kobak, Rita González-Márquez, Emoke-Ágnes Horvát, and Jan Lause. 2024 · 2024
Cited alongside, same era.
Dipper: Diversity in prompts for producing large language model ensembles in reasoning tasks
Gregory Kang Ruey Lau, Wenyang Hu, Diwen Liu, Jizhuo Chen, See-Kiong Ng, and Bryan Kian Hsiang Low. 2024 · 2024
Cited alongside, same era.
The ai scientist: Towards fully automated open-ended scientific discovery
Chris Lu, Cong Lu, Robert Tjarko Lange, Jakob Foerster, Jeff Clune, and David Ha. 2024 · 2024
Cited alongside, same era.
Gpt-4o mini: Advancing cost-efficient intelligence
OpenAI. 2024 · 2024
Cited alongside, same era.
Chenglei Si, Diyi Yang, and Tatsunori Hashimoto. 2024 · 2024
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Qwen2.5: A party of foundation models
Qwen Team. 2024 · 2024
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Qwen2-vl: Enhancing vision-language model’s perception of the world at any resolution
Peng Wang, Shuai Bai, Sinan Tan, Shijie Wang, Zhihao Fan, Jinze Bai, Keqin Chen, Xuejing Liu, Jialin Wang, Wenbin Ge, Yang Fan, Kai Dang, Mengfei Du, Xuancheng Ren, Rui Men, Dayiheng Liu, Chang Zhou, Jingren Zhou, and Junyang Lin. 2024 · 2024
Later among the works it cites.
Echoes in ai: Quantifying lack of plot diversity in llm outputs
Weijia Xu, Nebojsa Jojic, Sudha Rao, Chris Brockett, and Bill Dolan. 2024 · 2024
Later among the works it cites.
Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
DeepSeek-AI, Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Ruoyu Zhang, Runxin Xu, Qihao Zhu, Shirong Ma, Peiyi Wang, Xiao Bi, Xiaokang Zhang, Xingkai Yu, Yu Wu, Z. F. Wu, Zhibin Gou, Zhihong Shao, Zhuoshu Li, Ziyi Gao, and 181 others. 2025 · 2025
Closest in time.
Ielts writing scored essays dataset
Ibrahim Mazlumi. 2023 · 2025
Closest in time.
Llama 3.2 - 3b instruct model
MetaAI. 2025 · 2025
Closest in time.