Towards Reasoning Ability of Small Language Models

Language models are few-shot learners

Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D 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 Ziegler, Jeffrey Wu, Clemens Winter, and 12 others. 2020 · 1901

Earlier work this paper cites.

Think you have solved question answering? try arc, the ai2 reasoning challenge

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Earlier work this paper cites.

Can a suit of armor conduct electricity? a new dataset for open book question answering

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Earlier work this paper cites.

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Earlier work this paper cites.

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Earlier work this paper cites.

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Earlier work this paper cites.

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Earlier work this paper cites.

Training verifiers to solve math word problems

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Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, and John Schulman. 2021 · 2021

Earlier work this paper cites.

Knowledge distillation: A survey

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Earlier work this paper cites.

Measuring mathematical problem solving with the math dataset

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

Earlier work this paper cites.

Can large language models be an alternative to human evaluations?

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Earlier work this paper cites.

Palm: scaling language modeling with pathways

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Earlier work this paper cites.

Specializing smaller language models towards multi-step reasoning

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Earlier work this paper cites.

Efficient memory management for large language model serving with pagedattention

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Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph E. Gonzalez, Hao Zhang, and Ion Stoica. 2023 · 2023

Earlier work this paper cites.

Teaching small language models to reason

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Earlier work this paper cites.

Orca 2: Teaching small language models how to reason

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Arindam Mitra, Luciano Del Corro, Shweti Mahajan, Andres Codas, Clarisse Simoes, Sahaj Agarwal, Xuxi Chen, Anastasia Razdaibiedina, Erik Jones, Kriti Aggarwal, Hamid Palangi, Guoqing Zheng, Corby Rosset, Hamed Khanpour, and Ahmed Awadallah. 2023 · 2023

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Is ChatGPT a good NLG evaluator? a preliminary study

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Reasoning with large language models, a survey

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