Nova: An Iterative Planning and Search Approach to Enhance Novelty and Diversity of LLM Generated Ideas

The structure of scientific revolutions , volume 962

Thomas S Kuhn. 1997 · 1997

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Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents

Wenlong Huang, Pieter Abbeel, Deepak Pathak, and Igor Mordatch. 2022 · 2022

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Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, and Denny Zhou. 2022 · 2022

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REST MEETS REACT: SELF-IMPROVEMENT FOR MULTI-STEP REASONING LLM AGENT

Original

Renat Aksitov, Sobhan Miryoosefi, Zonglin Li, Daliang Li, Sheila Babayan, Kavya Kopparapu, Zachary Fisher, Ruiqi Guo, Sushant Prakash, Pranesh Srinivasan, Manzil Zaheer, Felix Yu, and Sanjiv Kumar. 2023 · 2023

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SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Original

Ning Miao, Yee Whye Teh, and Tom Rainforth. 2023 · 2023

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Reflexion: language agents with verbal reinforcement learning

Noah Shinn, Federico Cassano, Ashwin Gopinath, Karthik Narasimhan, and Shunyu Yao. 2023 · 2023

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Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions

Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, and Ashish Sabharwal. 2023 · 2023

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Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models

Lei Wang, Wanyu Xu, Yihuai Lan, Zhiqiang Hu, Yunshi Lan, Roy Ka-Wei Lee, and Ee-Peng Lim. 2023b · 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. 2023c · 2023

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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. 2023a · 2023

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ReAct: Synergizing Reasoning and Acting in Language Models

Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik R. Narasimhan, and Yuan Cao. 2023b · 2023

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Least-to-Most Prompting Enables Complex Reasoning in Large Language Models

Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Claire Cui, Olivier Bousquet, Quoc V. Le, and Ed H. Chi. 2023 · 2023

Cited alongside, same era.

ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models

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Jinheon Baek, Sujay Kumar Jauhar, Silviu Cucerzan, and Sung Ju Hwang. 2024 · 2024

MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation

Qian Huang, Jian Vora, Percy Liang, and Jure Leskovec. 2024 · 2024

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Mlr-copilot: Autonomous machine learning research based on large language models agents

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The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery

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Mathematical discoveries from program search with large language models

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Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers

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