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Numerous powerful large language models (LLMs) are now available for use as writing support tools, idea generators, and beyond.
Knowledge Consistency between Neural Networks and Beyond
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The dynamics of creative ideation: Introducing a new assessment paradigm
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With great training comes great vulnerability: Practical attacks against transfer learning. In 27th USENIX security symposium (USENIX Security 18) . 1281–1297
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"Forward flow": A new measure to quantify free thought and predict creativity
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Similarity of neural network representations revisited. In International conference on machine learning . PMLR, 3519–3529
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‘Revisiting model stitching to compare neural representations
Yamini Bansal, Preetum Nakkiran, and Boaz Barak. 2021 · 2021
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Measuring divergent thinking originality with human raters and text-mining models: A psychometric comparison of methods
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Algorithmic monoculture and social welfare
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Naming unrelated words predicts creativity
Jay A Olson, Johnny Nahas, Denis Chmoulevitch, Simon J Cropper, and Margaret E Webb. 2021 · 2021
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Picking on the same person: Does algorithmic monoculture lead to outcome homogenization?
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Putting GPT-3’s creativity to the (alternative uses) test
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Generative AI enhances individual creativity but reduces the collective diversity of novel content
Anil R. Doshi and Oliver P. Hauser. 2024 · 2024
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Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al · 2024
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How to Use AI to Enhance Your Storytelling Process
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Google + Team USA - Dear Sydney
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Self-assessment tests are unreliable measures of llm personality. In Proceedings of the 7th BlackboxNLP Workshop: Analyzing and Interpreting Neural Networks for NLP . 301–314
Akshat Gupta, Xiaoyang Song, and Gopala Anumanchipalli. 2024 · 2024
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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
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Probing the Creativity of Large Language Models: Can models produce divergent semantic association?
Honghua Chen and Nai Ding. 2023 · 2023
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Is artificial intelligence more creative than humans?: ChatGPT and the divergent association task
David Cropley. 2023 · 2023
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AQ Jiang, A Sablayrolles, A Mensch, C Bamford, DS Chaplot, D de las Casas, F Bressand, G Lengyel, G Lample, L Saulnier, et al · 2023
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Towards Measuring Representational Similarity of Large Language Models. In UniReps: the First Workshop on Unifying Representations in Neural Models
Max Klabunde, Mehdi Ben Amor, Michael Granitzer, and Florian Lemmerich. 2023 · 2023
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Using cognitive psychology to understand GPT-like models needs to extend beyond human biases
Massimo Stella, Thomas T Hills, and Yoed N Kenett. 2023 · 2023
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Getting aligned on representational alignment
Ilia Sucholutsky, Lukas Muttenthaler, Adrian Weller, Andi Peng, Andreea Bobu, Been Kim, Bradley C Love, Erin Grant, Iris Groen, Jascha Achterberg, et al · 2023
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The current state of artificial intelligence generative language models is more creative than humans on divergent thinking tasks
Kent F Hubert, Kim N Awa, and Darya L Zabelina. 2024 · 2024
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The platonic representation hypothesis
Minyoung Huh, Brian Cheung, Tongzhou Wang, and Phillip Isola. 2024 · 2024
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Bias Similarity Across Large Language Models
Hyejun Jeong, Shiqing Ma, and Amir Houmansadr. 2024 · 2024
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Sparse autoencoders reveal universal feature spaces across large language models
Michael Lan, Philip Torr, Austin Meek, Ashkan Khakzar, David Krueger, and Fazl Barez. 2024 · 2024
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Homogenizing Effect of Large Language Model (LLM) on Creative Diversity: An Empirical Comparison of Human and ChatGPT Writing
Kibum Moon, Adam Green, and Kostadin Kushlev. 2024 · 2024
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The Age of Generative AI: Over half of Americans have used generative AI and most believe it will help them be more creative
Vivek Pandya. 2024 · 2024
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Can llms generate novel research ideas? a large-scale human study with 100+ nlp researchers
Chenglei Si, Diyi Yang, and Tatsunori Hashimoto. 2024 · 2024
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Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Gemini Team, Petko Georgiev, Ving Ian Lei, Ryan Burnell, Libin Bai, Anmol Gulati, Garrett Tanzer, Damien Vincent, Zhufeng Pan, Shibo Wang, et al · 2024
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Jamba-1.5: Hybrid Transformer-Mamba Models at Scale
Jamba Team, Barak Lenz, Alan Arazi, Amir Bergman, Avshalom Manevich, Barak Peleg, Ben Aviram, Chen Almagor, Clara Fridman, Dan Padnos, et al · 2024
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Generative monoculture in large language models
Fan Wu, Emily Black, and Varun Chandrasekaran. 2024 · 2024
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Generative ai meets open-ended survey responses: Participant use of ai and homogenization
Simone Zhang, Janet Xu, and A Alvero. 2024 · 2024
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Assessing and understanding creativity in large language models
Yunpu Zhao, Rui Zhang, Wenyi Li, Di Huang, Jiaming Guo, Shaohui Peng, Yifan Hao, Yuanbo Wen, Xing Hu, Zidong Du, et al · 2024
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Generative artificial intelligence, human creativity, and art
Eric Zhou and Dokyun Lee. 2024 · 2024
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