System-2 Mathematical Reasoning via Enriched Instruction Tuning

Scaling laws for neural language models

Original

Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei. 2020 · 2001

Earlier work this paper cites.

Language models are few-shot learners

Original

Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeff Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Ma teusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2005

Earlier work this paper cites.

Adam: A method for stochastic optimization

Original

Diederik P Kingma and Jimmy Ba. 2014 · 2014

Earlier work this paper cites.

Thinking, fast and slow

Kahneman Daniel. 2017 · 2017

Earlier work this paper cites.

Improving language understanding by generative pre-training

Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al. 2018 · 2018

Earlier work this paper cites.

From human-human collaboration to human-ai collaboration: Designing ai systems that can work together with people

Dakuo Wang, Elizabeth Churchill, Pattie Maes, Xiangmin Fan, Ben Shneiderman, Yuanchun Shi, and Qianying Wang. 2020 · 2020

Earlier work this paper cites.

Training verifiers to solve math word problems

Original

Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, et al. 2021 · 2021

Earlier work this paper cites.

Measuring mathematical problem solving with the math dataset

Original

Dan Hendrycks, Collin Burns, Saurav Kadavath, Akul Arora, Steven Basart, Eric Tang, Dawn Song, and Jacob Steinhardt. 2021 · 2021

Earlier work this paper cites.

Learning to retrieve prompts for in-context learning

Original

Ohad Rubin, Jonathan Herzig, and Jonathan Berant. 2021 · 2021

Earlier work this paper cites.

Thinking fast and slow in large language models

Original

Thilo Hagendorff, Sarah Fabi, and Michal Kosinski. 2022 · 2022

Earlier work this paper cites.

A path towards autonomous machine intelligence version 0.9. 2, 2022-06-27

Yann LeCun. 2022 · 2022

Earlier work this paper cites.

A survey of deep learning for mathematical reasoning

Original

Pan Lu, Liang Qiu, Wenhao Yu, Sean Welleck, and Kai-Wei Chang. 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.

Self-consistency improves chain of thought reasoning in language models

Original

Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou. 2022 · 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 · 2022

Earlier work this paper cites.

React: Synergizing reasoning and acting in language models

Original

Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. 2022 · 2022

Earlier work this paper cites.

Automatic chain of thought prompting in large language models

Original

Zhuosheng Zhang, Aston Zhang, Mu Li, and Alex Smola. 2022 · 2022

Earlier work this paper cites.

Wall-e: World alignment by rule learning improves world model-based llm agents

Original

Siyu Zhou, Tianyi Zhou, Yijun Yang, Guodong Long, Deheng Ye, Jing Jiang, and Chengqi Zhang. 2024 · 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

Cited alongside, same era.

Rt-2: Vision-language-action models transfer web knowledge to robotic control

Original

Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Xi Chen, Krzysztof Choromanski, Tianli Ding, Danny Driess, Avinava Dubey, Chelsea Finn, et al. 2023 · 2023

Cited alongside, same era.

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 · 2023

Cited alongside, same era.

Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality

Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E Gonzalez, et al. 2023 · 2023

Cited alongside, same era.

Mammoth: Building math generalist models through hybrid instruction tuning

Original

Xiang Yue, Xingwei Qu, Ge Zhang, Yao Fu, Wenhao Huang, Huan Sun, Yu Su, and Wenhu Chen. 2023 · 2023

Later among the works it cites.

Deepseek llm: Scaling open-source language models with longtermism

Original

Xiao Bi, Deli Chen, Guanting Chen, Shanhuang Chen, Damai Dai, Chengqi Deng, Honghui Ding, Kai Dong, Qiushi Du, Zhe Fu, et al. 2024 · 2024

Closest in time.

Verified multi-step synthesis using large language models and monte carlo tree search

Original

David Brandfonbrener, Sibi Raja, Tarun Prasad, Chloe Loughridge, Jianang Yang, Simon Henniger, William E Byrd, Robert Zinkov, and Nada Amin. 2024 · 2024

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When is tree search useful for llm planning? it depends on the discriminator

Original

Ziru Chen, Michael White, Raymond Mooney, Ali Payani, Yu Su, and Huan Sun. 2024 · 2024

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