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Chemical reasoning usually involves complex, multi-step processes that demand precise calculations, where even minor errors can lead to cascading failures.
An evaluation of dual-process theories of reasoning
Magda Osman · 2004
Earlier work this paper cites.
Quantum chemistry
Donald A McQuarrie · 2008
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Curriculum learning
Yoshua Bengio, Jérôme Louradour, Ronan Collobert, and Jason Weston · 2009
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Multivariate data analysis
Joseph F Hair Jr, Wiliam C Black, Barry J Babin, and Rolph E Anderson · 2010
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Intelligence and the cognitive unconscious
Scott Barry Kaufman · 2011
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Physical chemistry: quanta, matter, and change
Peter Atkins, Julio De Paula, and Ronald Friedman · 2014
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Clevr: A diagnostic dataset for compositional language and elementary visual reasoning
Justin Johnson, Bharath Hariharan, Laurens Van Der Maaten, Li Fei-Fei, C Lawrence Zitnick, and Ross Girshick · 2017
Earlier work this paper cites.
Complexity-based prompting for multi-step reasoning
Yao Fu, Hao Peng, Ashish Sabharwal, Peter Clark, and Tushar Khot · 2022
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Decomposed prompting: A modular approach for solving complex tasks
Tushar Khot, Harsh Trivedi, Matthew Finlayson, Yao Fu, Kyle Richardson, Peter Clark, and Ashish Sabharwal · 2022
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Learn to explain: Multimodal reasoning via thought chains for science question answering
Pan Lu, Swaroop Mishra, Tanglin Xia, Liang Qiu, Kai-Wei Chang, Song-Chun Zhu, Oyvind Tafjord, Peter Clark, and Ashwin Kalyan · 2022
Earlier work this paper cites.
Is a question decomposition unit all we need?
Pruthvi Patel, Swaroop Mishra, Mihir Parmar, and Chitta Baral · 2022
Earlier work this paper cites.
The complexity of reasoning about and with chemical representations
Vicente Talanquer · 2022
Earlier work this paper cites.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
Earlier work this paper cites.
Large language models are reasoners with self-verification
Yixuan Weng, Minjun Zhu, Shizhu He, Kang Liu, and Jun Zhao · 2022
Earlier work this paper cites.
Atkins’ physical chemistry
Peter Atkins, Julio De Paula, and James Keeler · 2023
Earlier work this paper cites.
Autonomous chemical research with large language models
Daniil A. Boiko, Robert MacKnight, Ben Kline, and Gabe Gomes · 2023
Earlier work this paper cites.
ChemCrow: Augmenting large-language models with chemistry tools
Andres M Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D White, and Philippe Schwaller · 2023
Earlier work this paper cites.
KNIFE: Distilling meta-reasoning knowledge with free-text rationales
Aaron Chan, Zhiyuan Zeng, Wyatt Lake, Brihi Joshi, Hanjie Chen, and Xiang Ren · 2023
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Testing GPT-4 with wolfram alpha and code interpreter plug-ins on math and science problems
Ernest Davis and Scott Aaronson · 2023
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Promptbreeder: Self-referential self-improvement via prompt evolution
Chrisantha Fernando, Dylan Sunil Banarse, Henryk Michalewski, Simon Osindero, and Tim Rocktäschel · 2023
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Rarr: Researching and revising what language models say, using language models
Luyu Gao, Zhuyun Dai, Panupong Pasupat, Anthony Chen, Arun Tejasvi Chaganty, Yicheng Fan, Vincent Zhao, Ni Lao, Hongrae Lee, Da-Cheng Juan, et al · 2023
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Critic: Large language models can self-correct with tool-interactive critiquing
Zhibin Gou, Zhihong Shao, Yeyun Gong, Yujiu Yang, Nan Duan, Weizhu Chen, et al · 2023
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Language models, agent models, and world models: The law for machine reasoning and planning
Zhiting Hu and Tianmin Shu · 2023
Organa: A robotic assistant for automated chemistry experimentation and characterization
Kourosh Darvish, Marta Skreta, Yuchi Zhao, Naruki Yoshikawa, Sagnik Som, Miroslav Bogdanovic, Yang Cao, Han Hao, Haoping Xu, Alán Aspuru-Guzik, Animesh Garg, and Florian Shkurti · 2024
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SciKnowEval: Evaluating multi-level scientific knowledge of large language models
Kehua Feng, Keyan Ding, Weijie Wang, Xiang Zhuang, Zeyuan Wang, Ming Qin, Yu Zhao, Jianhua Yao, Qiang Zhang, and Huajun Chen · 2024
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Automated design of agentic systems
Shengran Hu, Cong Lu, and Jeff Clune · 2024
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From words to molecules: A survey of large language models in chemistry
Chang Liao, Yemin Yu, Yu Mei, and Ying Wei · 2024
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Large language models cannot self-correct reasoning yet
Jie Huang, Xinyun Chen, Swaroop Mishra, Huaixiu Steven Zheng, Adams Wei Yu, Xinying Song, and Denny Zhou · 2023
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Selfevolve: A code evolution framework via large language models
Shuyang Jiang, Yuhao Wang, and Yu Wang · 2023
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Design of chain-of-thought in math problem solving
Zhanming Jie, Trung Quoc Luong, Xinbo Zhang, Xiaoran Jin, and Hang Li · 2023
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Reflexion: an autonomous agent with dynamic memory and self-reflection
Noah Shinn, Beck Labash, and Ashwin Gopinath · 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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When do decompositions help for machine reading?
Kangda Wei, Dawn Lawrie, Benjamin Van Durme, Yunmo Chen, and Orion Weller · 2023
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Large language models as optimizers
Chengrun Yang, Xuezhi Wang, Yifeng Lu, Hanxiao Liu, Quoc V Le, Denny Zhou, and Xinyun Chen · 2023
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The llama 3 herd of models, July 2024
AI@Meta Llama Team · 2024
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Are large language models superhuman chemists?, 2024
Adrian Mirza, Nawaf Alampara, Sreekanth Kunchapu, Benedict Emoekabu, Aswanth Krishnan, Mara Wilhelmi, Macjonathan Okereke, Juliane Eberhardt, Amir Mohammad Elahi, Maximilian Greiner, Caroline T. Holick, Tanya Gupta, Mehrdad Asgari, Christina Glaubitz, Lea C. Klepsch, Yannik Köster, Jakob Meyer, Santiago Miret, Tim Hoffmann, Fabian Alexander Kreth, Michael Ringleb, Nicole Roesner, Ulrich S. Schubert, Leanne M. Stafast, Dinga Wonanke, Michael Pieler, Philippe Schwaller, and Kevin Maik Jablonka · 2024
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GPT-4 technical report, 2024
OpenAI, Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, et al · 2024
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Structured chemistry reasoning with large language models
Siru Ouyang, Zhuosheng Zhang, Bing Yan, Xuan Liu, Yejin Choi, Jiawei Han, and Lianhui Qin · 2024
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Leveraging biomolecule and natural language through multi-modal learning: A survey
Qizhi Pei, Lijun Wu, Kaiyuan Gao, Jinhua Zhu, Yue Wang, Zun Wang, Tao Qin, and Rui Yan · 2024
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Investigate-consolidate-exploit: A general strategy for inter-task agent self-evolution
Cheng Qian, Shihao Liang, Yujia Qin, Yining Ye, Xin Cong, Yankai Lin, Yesai Wu, Zhiyuan Liu, and Maosong Sun · 2024
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Recursive introspection: Teaching language model agents how to self-improve
Yuxiao Qu, Tianjun Zhang, Naman Garg, and Aviral Kumar · 2024
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Replan: Robotic replanning with perception and language models
Marta Skreta, Zihan Zhou, Jia Lin Yuan, Kourosh Darvish, Alán Aspuru-Guzik, and Animesh Garg · 2024
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SciRIFF: A resource to enhance language model instruction-following over scientific literature
David Wadden, Kejian Shi, Jacob Morrison, Aakanksha Naik, Shruti Singh, Nitzan Barzilay, Kyle Lo, Tom Hope, Luca Soldaini, Shannon Zejiang Shen, et al · 2024
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Bridging text and molecule: A survey on multimodal frameworks for molecule
Yi Xiao, Xiangxin Zhou, Qiang Liu, and Liang Wang · 2024
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Buffer of thoughts: Thought-augmented reasoning with large language models
Ling Yang, Zhaochen Yu, Tianjun Zhang, Shiyi Cao, Minkai Xu, Wentao Zhang, Joseph E Gonzalez, and Bin Cui · 2024
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Tree of thoughts: Deliberate problem solving with large language models
Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Tom Griffiths, Yuan Cao, and Karthik Narasimhan · 2024
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Symbolic learning enables self-evolving agents
Wangchunshu Zhou, Yixin Ou, Shengwei Ding, Long Li, Jialong Wu, Tiannan Wang, Jiamin Chen, Shuai Wang, Xiaohua Xu, Ningyu Zhang, et al · 2024
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