CS4: Measuring the Creativity of Large Language Models Automatically by Controlling the Number of Story-Writing Constraints

Encoding specificity and retrieval processes in episodic memory

Endel Tulving and Donald M Thomson. 1973 · 1973

Earlier work this paper cites.

A diversity-promoting objective function for neural conversation models

Jiwei Li, Michel Galley, Chris Brockett, Jianfeng Gao, and Bill Dolan. 2016 · 2016

Earlier work this paper cites.

Hierarchical neural story generation

Original

Angela Fan, Mike Lewis, and Yann Dauphin. 2018 · 2018

Earlier work this paper cites.

Unifying human and statistical evaluation for natural language generation

Tatsunori B Hashimoto, Hugh Zhang, and Percy Liang. 2019 · 2019

Earlier work this paper cites.

Creative writing with an ai-powered writing assistant: Perspectives from professional writers

Original

Daphne Ippolito, Ann Yuan, Andy Coenen, and Sehmon Burnam. 2022 · 2022

Earlier work this paper cites.

Augmenting scientific creativity with an analogical search engine

Hyeonsu B Kang, Xin Qian, Tom Hope, Dafna Shahaf, Joel Chan, and Aniket Kittur. 2022 · 2022

Earlier work this paper cites.

Contrastive decoding: Open-ended text generation as optimization

Original

Xiang Lisa Li, Ari Holtzman, Daniel Fried, Percy Liang, Jason Eisner, Tatsunori Hashimoto, Luke Zettlemoyer, and Mike Lewis. 2022 · 2022

Earlier work this paper cites.

Training language models to follow instructions with human feedback

Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022 · 2022

Earlier work this paper cites.

Gpt-4 technical report

Original

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

Earlier work this paper cites.

The crowdless future? generative ai and creative problem solving

Leonard Boussioux, Jacqueline Ng Lane, Miaomiao Zhang, Vladimir Jacimovic, and Karim R Lakhani. 2023 · 2023

Earlier work this paper cites.

Speak, memory: An archaeology of books known to chatgpt/gpt-4

Original

Kent K Chang, Mackenzie Cramer, Sandeep Soni, and David Bamman. 2023 · 2023

Earlier work this paper cites.

A closer look into using large language models for automatic evaluation

Cheng-Han Chiang and Hung-yi Lee. 2023 · 2023

Earlier work this paper cites.

Fluid transformers and creative analogies: Exploring large language models’ capacity for augmenting cross-domain analogical creativity

Zijian Ding, Arvind Srinivasan, Stephen MacNeil, and Joel Chan. 2023 · 2023

Earlier work this paper cites.

Chatgpt outperforms crowd workers for text-annotation tasks

Fabrizio Gilardi, Meysam Alizadeh, and Maël Kubli. 2023 · 2023

Earlier work this paper cites.

A confederacy of models: A comprehensive evaluation of llms on creative writing

Original

Carlos Gómez-Rodríguez and Paul Williams. 2023 · 2023

Earlier work this paper cites.

Sok: Memorization in general-purpose large language models

Original

Valentin Hartmann, Anshuman Suri, Vincent Bindschaedler, David Evans, Shruti Tople, and Robert West. 2023 · 2023

Earlier work this paper cites.

Preventing generation of verbatim memorization in language models gives a false sense of privacy

Daphne Ippolito, Florian Tramer, Milad Nasr, Chiyuan Zhang, Matthew Jagielski, Katherine Lee, Christopher Choquette Choo, and Nicholas Carlini. 2023 · 2023

Earlier work this paper cites.

G-eval: Nlg evaluation using gpt-4 with better human alignment

Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, and Chenguang Zhu. 2023 · 2023

Earlier work this paper cites.

A long way to go: Investigating length correlations in rlhf

Original

Prasann Singhal, Tanya Goyal, Jiacheng Xu, and Greg Durrett. 2023 · 2023

Cited alongside, same era.

Llama 2: Open foundation and fine-tuned chat models

Original

Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al. 2023 · 2023

Cited alongside, same era.

The generative ai paradox:“what it can create, it may not understand

Peter West, Ximing Lu, Nouha Dziri, Faeze Brahman, Linjie Li, Jena D Hwang, Liwei Jiang, Jillian Fisher, Abhilasha Ravichander, Khyathi Chandu, et al. 2023 · 2023

Cited alongside, same era.

Reasoning or reciting? exploring the capabilities and limitations of language models through counterfactual tasks

Original

Zhaofeng Wu, Linlu Qiu, Alexis Ross, Ekin Akyürek, Boyuan Chen, Bailin Wang, Najoung Kim, Jacob Andreas, and Yoon Kim. 2023 · 2023

Cited alongside, same era.

Exploring precision and recall to assess the quality and diversity of llms

Florian Le Bronnec, Alexandre Vérine, Benjamin Negrevergne, Yann Chevaleyre, and Alexandre Allauzen. 2024 · 2024

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How ai processing delays foster creativity: Exploring research question co-creation with an llm-based agent

Yiren Liu, Si Chen, Haocong Cheng, Mengxia Yu, Xiao Ran, Andrew Mo, Yiliu Tang, and Yun Huang. 2024 · 2024

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Llm comparative assessment: Zero-shot nlg evaluation through pairwise comparisons using large language models

Adian Liusie, Potsawee Manakul, and Mark Gales. 2024 · 2024

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Benchmarking language model creativity: A case study on code generation

Original

Yining Lu, Dixuan Wang, Tianjian Li, Dongwei Jiang, and Daniel Khashabi. 2024 · 2024

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Pron vs prompt: Can large language models already challenge a world-class fiction author at creative text writing?

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