Evaluating Mathematical Reasoning Beyond Accuracy

Decoupled Weight Decay Regularization

Loshchilov, I.; and Hutter, F. 2019 · 2019

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A Study of Automatic Metrics for the Evaluation of Natural Language Explanations

Clinciu, M.-A.; Eshghi, A.; and Hastie, H. 2021 · 2021

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Training verifiers to solve math word problems

Original

Cobbe, K.; Kosaraju, V.; Bavarian, M.; Chen, M.; Jun, H.; Kaiser, L.; Plappert, M.; Tworek, J.; Hilton, J.; Nakano, R.; et al. 2021 · 2021

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Measuring Mathematical Problem Solving With the MATH Dataset

Hendrycks, D.; Burns, C.; Kadavath, S.; Arora, A.; Basart, S.; Tang, E.; Song, D.; and Steinhardt, J. 2021 · 2021

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ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoning

Golovneva, O.; Chen, M. P.; Poff, S.; Corredor, M.; Zettlemoyer, L.; Fazel-Zarandi, M.; and Celikyilmaz, A. 2022 · 2022

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Solving quantitative reasoning problems with language models

Lewkowycz, A.; Andreassen, A.; Dohan, D.; Dyer, E.; Michalewski, H.; Ramasesh, V.; Slone, A.; Anil, C.; Schlag, I.; Gutman-Solo, T.; et al. 2022 · 2022

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Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought

Saparov, A.; and He, H. 2022 · 2022

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Solving math word problems with process-and outcome-based feedback

Original

Uesato, J.; Kushman, N.; Kumar, R.; Song, F.; Siegel, N.; Wang, L.; Creswell, A.; Irving, G.; and Higgins, I. 2022 · 2022

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Llemma: An Open Language Model for Mathematics

Azerbayev, Z.; Schoelkopf, H.; Paster, K.; Dos Santos, M.; McAleer, S. M.; Jiang, A. Q.; Deng, J.; Biderman, S.; and Welleck, S. 2023 · 2023

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Generative AI for Math: Abel

Chern, E.; Zou, H.; Li, X.; Hu, J.; Feng, K.; Li, J.; and Liu, P. 2023 · 2023

Cited alongside, same era.

Safe RLHF: Safe Reinforcement Learning from Human Feedback

Dai, J.; Pan, X.; Sun, R.; Ji, J.; Xu, X.; Liu, M.; Wang, Y.; and Yang, Y. 2023 · 2023

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Mistral 7B

Original

Jiang, A. Q.; Sablayrolles, A.; Mensch, A.; Bamford, C.; Chaplot, D. S.; Casas, D. d. l.; Bressand, F.; Lengyel, G.; Lample, G.; Saulnier, L.; et al. 2023 · 2023

Cited alongside, same era.

Let’s Verify Step by Step

Lightman, H.; Kosaraju, V.; Burda, Y.; Edwards, H.; Baker, B.; Lee, T.; Leike, J.; Schulman, J.; Sutskever, I.; and Cobbe, K. 2023 · 2023

Cited alongside, same era.

A Survey of Deep Learning for Mathematical Reasoning

Lu, P.; Qiu, L.; Yu, W.; Welleck, S.; and Chang, K.-W. 2023 · 2023

Cited alongside, same era.

Wizardmath: Empowering mathematical reasoning for large language models via reinforced evol-instruct

Arb: Advanced reasoning benchmark for large language models

Original

Sawada, T.; Paleka, D.; Havrilla, A.; Tadepalli, P.; Vidas, P.; Kranias, A.; Nay, J. J.; Gupta, K.; and Komatsuzaki, A. 2023 · 2023

Later among the works it cites.

Llama 2: Open foundation and fine-tuned chat models

Original

Touvron, H.; Martin, L.; Stone, K.; Albert, P.; Almahairi, A.; Babaei, Y.; Bashlykov, N.; Batra, S.; Bhargava, P.; Bhosale, S.; et al. 2023 · 2023

Later among the works it cites.

LLMs cannot find reasoning errors, but can correct them!

Original

Tyen, G.; Mansoor, H.; Chen, P.; Mak, T.; and Cărbune, V. 2023 · 2023

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Math-Shepherd: A Label-Free Step-by-Step Verifier for LLMs in Mathematical Reasoning

Original

Wang, P.; Li, L.; Shao, Z.; Xu, R.; Dai, D.; Li, Y.; Chen, D.; Wu, Y.; and Sui, Z. 2023 · 2023

Later among the works it cites.