Naturalprover: Grounded mathematical proof generation with language models
Sean Welleck, Jiacheng Liu, Ximing Lu, Hannaneh Hajishirzi, and Yejin Choi · 2022
Later among the works it cites.
Draft, sketch, and prove: Guiding formal theorem provers with informal proofs
Original
Albert Q. Jiang, Sean Welleck, Jin Peng Zhou, Wenda Li, Jiacheng Liu, Mateja Jamnik, Timothée Lacroix, Yuhuai Wu, and Guillaume Lample · 2022
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Thor: Wielding hammers to integrate language models and automated theorem provers
Albert Q. Jiang, Wenda Li, Szymon Tworkowski, Konrad Czechowski, Tomasz Odrzygóźdź, Piotr Miłoś, Yuhuai Wu, and Mateja Jamnik · 2022
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LEMMA: Bootstrapping high-level mathematical reasoning with learned symbolic abstractions
Original
Zhening Li, Gabriel Poesia, Omar Costilla-Reyes, Noah Goodman, and Armando Solar-Lezama · 2022
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Capturing advanced human cognitive abilities with deep neural networks
James L. McClelland · 2022
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Symbols and mental programs: a hypothesis about human singularity
Stanislas Dehaene, Fosca Al Roumi, Yair Lakretz, Samuel Planton, and Mathias Sablé-Meyer · 2022
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A language of thought for the mental representation of geometric shapes
Mathias Sablé-Meyer, Kevin Ellis, Josh Tenenbaum, and Stanislas Dehaene · 2022
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Emergent world representations: Exploring a sequence model trained on a synthetic task
Original
Kenneth Li, Aspen K. Hopkins, David Bau, Fernanda Viégas, Hanspeter Pfister, and Martin Wattenberg · 2022
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Deep learning, reinforcement learning, and world models
Yutaka Matsuo, Yann LeCun, Maneesh Sahani, Doina Precup, David Silver, Masashi Sugiyama, Eiji Uchibe, and Jun Morimoto · 2022
Later among the works it cites.
The evolution of agency: Behavioral organization from lizards to humans
Michael Tomasello · 2022
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People construct simplified mental representations to plan
Mark K. Ho, David Abel, Carlos G. Correa, Michael L. Littman, Jonathan D. Cohen, and Thomas L. Griffiths · 2022
Later among the works it cites.
Planning with theory of mind
Mark K. Ho, Rebecca Saxe, and Fiery Cushman · 2022
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Training compute-optimal large language models
Original
Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya, Trevor Cai, Eliza Rutherford, Diego de Las Casas, Lisa Anne Hendricks, Johannes Welbl, Aidan Clark, et al · 2022
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Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed H. Chi, Quoc V. Le, Denny Zhou, et al · 2022
Later among the works it cites.
Star: Bootstrapping reasoning with reasoning
Eric Zelikman, Yuhuai Wu, Jesse Mu, and Noah Goodman · 2022
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Human-level play in the game of diplomacy by combining language models with strategic reasoning
Meta Fundamental AI Research Diplomacy Team (FAIR)†, Anton Bakhtin, Noam Brown, Emily Dinan, Gabriele Farina, Colin Flaherty, Daniel Fried, Andrew Goff, Jonathan Gray, Hengyuan Hu, et al · 2022
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Gpt-4 technical report, 2023
OpenAI · 2023
Closest in time.
Sparks of artificial general intelligence: Early experiments with gpt-4
Original
Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, et al · 2023
Closest in time.
Evaluating language models for mathematics through interactions
Original
Katherine M Collins, Albert Q Jiang, Simon Frieder, Lionel Wong, Miri Zilka, Umang Bhatt, Thomas Lukasiewicz, Yuhuai Wu, Joshua B Tenenbaum, William Hart, et al · 2023
Closest in time.
Mathematical capabilities of chatgpt
Original
Simon Frieder, Luca Pinchetti, Ryan-Rhys Griffiths, Tommaso Salvatori, Thomas Lukasiewicz, Philipp Christian Petersen, Alexis Chevalier, and Julius Berner · 2023
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An empirical study on challenging math problem solving with gpt-4
Original
Yiran Wu, Feiran Jia, Shaokun Zhang, Qingyun Wu, Hangyu Li, Erkang Zhu, Yue Wang, Yin Tat Lee, Richard Peng, and Chi Wang · 2023
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Faith and fate: Limits of transformers on compositionality
Original
Nouha Dziri, Ximing Lu, Melanie Sclar, Xiang Lorraine Li, Liwei Jian, Bill Yuchen Lin, Peter West, Chandra Bhagavatula, Ronan Le Bras, Jena D Hwang, et al · 2023
Closest in time.
Wizardmath: Empowering mathematical reasoning for large language models via reinforced evol-instruct
Original
Haipeng Luo, Qingfeng Sun, Can Xu, Pu Zhao, Jianguang Lou, Chongyang Tao, Xiubo Geng, Qingwei Lin, Shifeng Chen, and Dongmei Zhang · 2023
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Let’s verify step by step
Original
Hunter Lightman, Vineet Kosaraju, Yura Burda, Harri Edwards, Bowen Baker, Teddy Lee, Jan Leike, John Schulman, Ilya Sutskever, and Karl Cobbe · 2023
Closest in time.
Metamath: Bootstrap your own mathematical questions for large language models
Original
Longhui Yu, Weisen Jiang, Han Shi, Jincheng Yu, Zhengying Liu, Yu Zhang, James T. Kwok, Zhenguo Li, Adrian Weller, and Weiyang Liu · 2023
Closest in time.
Textbooks are all you need
Original
Suriya Gunasekar, Yi Zhang, Jyoti Aneja, Caio César Teodoro Mendes, Allie Del Giorno, Sivakanth Gopi, Mojan Javaheripi, Piero Kauffmann, Gustavo de Rosa, Olli Saarikivi, et al · 2023
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Testing GPT-4 with Wolfram Alpha and Code Interpreter plug-ins on math and science problems
Original
Ernest Davis and Scott Aaronson · 2023
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Baldur: Whole-proof generation and repair with large language models
Original
Emily First, Markus N. Rabe, Talia Ringer, and Yuriy Brun · 2023
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Solving math word problems by combining language models with symbolic solvers
Original
Joy He-Yueya, Gabriel Poesia, Rose E. Wang, and Noah D. Goodman · 2023
Closest in time.
Peano: learning formal mathematical reasoning
Gabriel Poesia and Noah D. Goodman · 2023
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Word meaning in minds and machines
Brenden M. Lake and Gregory L. Murphy · 2023
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From word models to world models: Translating from natural language to the probabilistic language of thought
Original
Lionel Wong, Gabriel Grand, Alexander K. Lew, Noah D. Goodman, Vikash K. Mansinghka, Jacob Andreas, and Joshua B. Tenenbaum · 2023
Closest in time.
Augmented language models: A survey
Original
Grégoire Mialon, Roberto Dessì, Maria Lomeli, Christoforos Nalmpantis, Ram Pasunuru, Roberta Raileanu, Baptiste Rozière, Timo Schick, Jane Dwivedi-Yu, Asli Celikyilmaz, et al · 2023
Closest in time.
What makes mathematicians believe unproved mathematical statements?
Timothy Gowers · 2023
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Humans decompose tasks by trading off utility and computational cost
Carlos G. Correa, Mark K. Ho, Frederick Callaway, Nathaniel D. Daw, and Thomas L. Griffiths · 2023
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Rational simplification and rigidity in human planning
Mark K. Ho, Jonathan D. Cohen, and Thomas L. Griffiths · 2023
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Resource rationality
Thomas Icard · 2023
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Reflexion: Language agents with verbal reinforcement learning
Original
Noah Shinn, Federico Cassano, Beck Labash, Ashwin Gopinath, Karthik Narasimhan, and Shunyu Yao · 2023
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Using games to understand the mind
Kelsey Allen, Franziska Brändle, Matthew Botvinick, Judith E. Fan, Samuel J. Gershman, Alison Gopnik, Thomas L. Griffiths, Joshua K. Hartshorne, Tobias U. Hauser, Mark K. Ho, Joshua R. de Leeuw, Wei Ji Ma, Kou Murayama, Jonathan D. Nelson, Bas van Opheusden, Thomas Pouncy, Janet Rafner, Iyad Rahwan, Robb Rutledge, Jacob Friis Sherson, Ozgur Simsek, Hugo Spiers, Christopher Summerfield, Mirko Thalmann, Natalia Vélez, Andrew J. Watrous, Joshua B. Tenenbaum, and Eric Schulz · 2023
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Research agenda
Gabriel Poesia · 2023
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