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Scientific discovery plays a pivotal role in advancing human society, and recent progress in large language models (LLMs) suggests their potential to accelerate this process.
The act of creation
Arthur Koestler · 1964
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Undiscovered public knowledge
Don R Swanson · 1986
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Research methods for business
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Associative abilities underlying creativity
Mathias Benedek, Tanja Könen, and Aljoscha C Neubauer · 2012
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Why do nations produce science advances and new technology?
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Unsupervised word embeddings capture latent knowledge from materials science literature
Vahe Tshitoyan, John Dagdelen, Leigh Weston, Alexander Dunn, Ziqin Rong, Olga Kononova, Kristin A. Persson, Gerbrand Ceder, and Anubhav Jain · 2019
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Autonomous chemical research with large language models
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Universal self-consistency for large language model generation
Xinyun Chen, Renat Aksitov, Uri Alon, Jie Ren, Kefan Xiao, Pengcheng Yin, Sushant Prakash, Charles Sutton, Xuezhi Wang, and Denny Zhou · 2023
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Self-refine: Iterative refinement with self-feedback
Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Shashank Gupta, Bodhisattwa Prasad Majumder, Katherine Hermann, Sean Welleck, Amir Yazdanbakhsh, and Peter Clark · 2023
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Henry Sprueill, Carl Edwards, Mariefel V. Olarte, Udishnu Sanyal, Heng Ji, and Sutanay Choudhury · 2023
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Self-consistency improves chain of thought reasoning in language models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou · 2023
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End-to-end case-based reasoning for commonsense knowledge base completion
Zonglin Yang, Xinya Du, Erik Cambria, and Claire Cardie · 2023
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Zonglin Yang, Xinya Du, Rui Mao, Jinjie Ni, and Erik Cambria · 2023
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Large language models are zero shot hypothesis proposers
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CHEMREASONER: heuristic search over a large language model’s knowledge space using quantum-chemical feedback
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