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Current LLM training positions mathematical reasoning as a core capability.
Crafting papers on machine learning
Langley, P · 2000
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Measuring mathematical problem solving with the math dataset, 2021
Hendrycks, D., Burns, C., Kadavath, S., Arora, A., Basart, S., Tang, E., Song, D., and Steinhardt, J · 2021
Earlier work this paper cites.
Measuring progress on scalable oversight for large language models, 2022
Bowman, S. and etal · 2022
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Unnatural instructions: Tuning language models with (almost) no human labor
Honovich, O., Scialom, T., Levy, O., and Schick, T · 2022
Earlier work this paper cites.
Chain-of-thought prompting elicits reasoning in large language models
Wei, J., Wang, X., Liu, Q., Yang, B., Dong, X., Huang, H., and Wang, W · 2022
Earlier work this paper cites.
Achiam, J., Adler, S., Agarwal, S., Ahmad, L., Akkaya, I., Aleman, F. L., Almeida, D., Altenschmidt, J., Altman, S., Anadkat, S., et al · 2023
Earlier work this paper cites.
Anil, R., Dai, A. M., Firat, O., Johnson, M., Lepikhin, D., Passos, A., Shakeri, S., Taropa, E., Bailey, P., Chen, Z., et al · 2023
Earlier work this paper cites.
A theory for emergence of complex skills in language models
Arora, S. and Goyal, A · 2023
Earlier work this paper cites.
Palm: Scaling language modeling with pathways
Chowdhery, A., Narang, S., Devlin, J., Bosma, M., Mishra, G., Roberts, A., Barham, P., Chung, H. W., Sutton, C., Gehrmann, S., Schuh, P., Shi, K., Tsvyashchenko, S., Maynez, J., Rao, A., Barnes, P., Tay, Y., Shazeer, N., Prabhakaran, V., Reif, E., Du, N., Hutchinson, B., Pope, R., Bradbury, J., Austin, J., Isard, M., Gur-Ari, G., Yin, P., Duke, T., Levskaya, A., Ghemawat, S., Dev, S., Michalewski, H., Garcia, X., Misra, V., Robinson, K., Fedus, L., Zhou, D., Ippolito, D., Luan, D., Lim, H., Zoph, B., Spiridonov, A., Sepassi, R., Dohan, D., Agrawal, S., Omernick, M., Dai, A. M., Pillai, T. S., Pellat, M., Lewkowycz, A., Moreira, E., Child, R., Polozov, O., Lee, K., Zhou, Z., Wang, X., Saeta, B., Diaz, M., Firat, O., Catasta, M., Wei, J., Meier-Hellstern, K., Eck, D., Dean, J., Petrov, S., and Fiedel, N · 2023
Earlier work this paper cites.
Gunasekar, S., Zhang, Y., Aneja, J., Mendes, C. C. T., Del Giorno, A., Gopi, S., Javaheripi, M., Kauffmann, P., de Rosa, G., Saarikivi, O., et al · 2023
Earlier work this paper cites.
Targen: Targeted data generation with large language models
Gupta, H., Scaria, K., Anantheswaran, U., Verma, S., Parmar, M., Sawant, S. A., Mishra, S., and Baral, C · 2023
Earlier work this paper cites.
Efficient memory management for large language model serving with pagedattention
Kwon, W., Li, Z., Zhuang, S., Sheng, Y., Zheng, L., Yu, C. H., Gonzalez, J., Zhang, H., and Stoica, I · 2023
Earlier work this paper cites.
Gpt-4 technical report, 2023
OpenAI · 2023
Earlier work this paper cites.
Gemini: A family of highly capable multimodal models, 2023
Team, G · 2023
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Gemini: a family of highly capable multimodal models
Team, G., Anil, R., Borgeaud, S., Wu, Y., Alayrac, J.-B., Yu, J., Soricut, R., Schalkwyk, J., Dai, A. M., Hauth, A., et al · 2023
Cited alongside, same era.
Llama 2: Open foundation and fine-tuned chat models
Touvron, H., Martin, L., Stone, K., Albert, P., Almahairi, A., Babaei, Y., Bashlykov, N., Batra, S., Bhargava, P., Bhosale, S., et al · 2023
Cited alongside, same era.
Metamath: Bootstrap your own mathematical questions for large language models
Yu, L., Jiang, W., Shi, H., Yu, J., Liu, Z., Zhang, Y., Kwok, J. T., Li, Z., Weller, A., and Liu, W · 2023
Cited alongside, same era.
Mammoth: Building math generalist models through hybrid instruction tuning
Lu, Z., Zhou, A., Ren, H., Wang, K., Shi, W., Pan, J., Zhan, M., and Li, H · 2024
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Gsm-symbolic: Understanding the limitations of mathematical reasoning in large language models
Mirzadeh, I., Alizadeh, K., Shahrokhi, H., Tuzel, O., Bengio, S., and Farajtabar, M · 2024
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Openai o1 system card
OpenAI · 2024
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Datadreamer: A tool for synthetic data generation and reproducible llm workflows
Patel, A., Raffel, C., and Callison-Burch, C · 2024
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Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Reid, M., Savinov, N., Teplyashin, D., Lepikhin, D., Lillicrap, T., Alayrac, J.-b., Soricut, R., Lazaridou, A., Firat, O., Schrittwieser, J., et al · 2024
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Yue, X., Qu, X., Zhang, G., Fu, Y., Huang, W., Sun, H., Su, Y., and Chen, W · 2023
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Phi-3 technical report: A highly capable language model locally on your phone
Abdin, M., Jacobs, S. A., Awan, A. A., Aneja, J., Awadallah, A., Awadalla, H., Bach, N., Bahree, A., Bakhtiari, A., Behl, H., et al · 2024
Cited alongside, same era.
Claude 3.5 sonnet model card addendum
Anthropic · 2024
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Scaling synthetic data creation with 1,000,000,000 personas
Chan, X., Wang, X., Yu, D., Mi, H., and Yu, D · 2024
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Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem solving
Didolkar, A., Goyal, A., Ke, N. R., Guo, S., Valko, M., Lillicrap, T., Rezende, D., Bengio, Y., Mozer, M. C., and Arora, S · 2024
Cited alongside, same era.
Dubey, A., Jauhri, A., Pandey, A., Kadian, A., Al-Dahle, A., Letman, A., Mathur, A., Schelten, A., Yang, A., Fan, A., et al · 2024
Cited alongside, same era.
Key-point-driven data synthesis with its enhancement on mathematical reasoning
Huang, Y., Liu, X., Gong, Y., Gou, Z., Shen, Y., Duan, N., and Chen, W · 2024
Cited alongside, same era.
Mixtral of experts, 2024
Jiang, A. Q., Sablayrolles, A., Roux, A., Mensch, A., Savary, B., Bamford, C., Chaplot, D. S., de las Casas, D., Hanna, E. B., Bressand, F., Lengyel, G., Bour, G., Lample, G., Lavaud, L. R., Saulnier, L., Lachaux, M.-A., Stock, P., Subramanian, S., Yang, S., Antoniak, S., Scao, T. L., Gervet, T., Lavril, T., Wang, T., Lacroix, T., and Sayed, W. E · 2024
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Deepseekmath: Pushing the limits of mathematical reasoning in open language models
Shao, Z., Wang, P., Zhu, Q., Xu, R., Song, J., Zhang, M., Li, Y., Wu, Y., and Guo, D · 2024
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Openmathinstruct-1: A 1.8 million math instruction tuning dataset
Toshniwal, S., Moshkov, I., Narenthiran, S., Gitman, D., Jia, F., and Gitman, I · 2024
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Solving olympiad geometry without human demonstrations
Trinh, T. H., Wu, Y., Le, Q. V., He, H., and Luong, T · 2024
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Yang, A., Yang, B., Zhang, B., Hui, B., Zheng, B., Yu, B., Li, C., Liu, D., Huang, F., Wei, H., et al · 2024
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Large language model as attributed training data generator: A tale of diversity and bias
Yu, Y., Zhuang, Y., Zhang, J., Meng, Y., Ratner, A. J., Krishna, R., Shen, J., and Zhang, C · 2024
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A careful examination of large language model performance on grade school arithmetic
Zhang, H., Da, J., Lee, D., Robinson, V., Wu, C., Song, W., Zhao, T., Raja, P., Slack, D., Lyu, Q., et al · 2024
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
Guo, D., Yang, D., Zhang, H., Song, J., Zhang, R., Xu, R., Zhu, Q., Ma, S., Wang, P., Bi, X., et al · 2025
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