The Effect of Sampling Temperature on Problem Solving in Large Language Models

P. Jaccard, “The distribution of flora in the alpine zone,” New Phytologist , vol. 11, pp. 37–50, 2 1912

1912

Earlier work this paper cites.

W. H. Kruskal and W. A. Wallis, “Use of ranks in one-criterion variance analysis,” Journal of the American Statistical Association , vol. 47, no. 260, pp. 583–621, 1952. [Online]. Available: https://www.tandfonline.com/doi/abs/10.1080/01621459.1952.10483441

1952

Earlier work this paper cites.

Z. S. Harris, “Distributional structure,” WORD , vol. 10, pp. 146–162, 8 1954

1954

Earlier work this paper cites.

O. J. Dunn, “Multiple comparisons using rank sums,” Technometrics , vol. 6, no. 3, pp. 241–252, 1964. [Online]. Available: https://www.tandfonline.com/doi/abs/10.1080/00401706.1964.10490181

1964

Earlier work this paper cites.

V. Levenshtein, “Binary codes capable of correcting deletions, insertions and reversals,” Soviet Physics Doklady , vol. 10, pp. 707–710, 1966

1966

Earlier work this paper cites.

K. S. Jones, “A statistical interpretation of term specificity and its application in retrieval,” Journal of Documentation , vol. 28, pp. 11–21, 1 1972

1972

Earlier work this paper cites.

D. H. Ackley, G. E. Hinton, and T. J. Sejnowski, “A learning algorithm for Boltzmann machines,” Cognitive Science , vol. 9, pp. 147–169, 1985

1985

Earlier work this paper cites.

K. Papineni, S. Roukos, T. Ward, and W.-J. Zhu, “BLEU,” in Proceedings of the 40th Annual Meeting on Association for Computational Linguistics - ACL ’02 . Association for Computational Linguistics, 2001, p. 311

2001

Earlier work this paper cites.

I. Ward, “JSON lines,” 2014. [Online]. Available: https://jsonlines.org/

2014

Earlier work this paper cites.

G. Hinton, O. Vinyals, and J. Dean, “Distilling the knowledge in a neural network,” arXiv , 3 2015

2015

Earlier work this paper cites.

P. Clark, I. Cowhey, O. Etzioni, T. Khot, A. Sabharwal, C. Schoenick, and O. Tafjord, “Think you have solved question answering? Try ARC, the AI2 reasoning challenge,” ArXiv , 3 2018

2018

Earlier work this paper cites.

R. Zellers, A. Holtzman, Y. Bisk, A. Farhadi, and Y. Choi, “HellaSwag: Can a machine really finish your sentence?” in Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics , 2019

2019

Earlier work this paper cites.

N. Reimers and I. Gurevych, “Sentence-BERT: Sentence embeddings using Siamese BERT-networks,” in Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing . Association for Computational Linguistics, 8 2019

2019

Earlier work this paper cites.

P.-H. Wang, S.-I. Hsieh, S.-C. Chang, Y.-T. Chen, J.-Y. Pan, W. Wei, and D.-C. Juan, “Contextual temperature for language modeling,” arXiv , 12 2020

2020

Earlier work this paper cites.

J. Liu, L. Cui, H. Liu, D. Huang, Y. Wang, and Y. Zhang, “Logiqa: A challenge dataset for machine reading comprehension with logical reasoning,” in International Joint Conference on Artificial Intelligence , 2020

2020

Earlier work this paper cites.

S. Wang, Z. Liu, W. Zhong, M. Zhou, Z. Wei, Z. Chen, and N. Duan, “From lsat: The progress and challenges of complex reasoning,” IEEE/ACM Transactions on Audio, Speech and Language Processing , vol. 30, pp. 2201–2216, 8 2021

2021

Earlier work this paper cites.

F. F. Xu, U. Alon, G. Neubig, and V. J. Hellendoorn, “A systematic evaluation of large language models of code,” in Proceedings of the 6th ACM SIGPLAN International Symposium on Machine Programming . Association for Computing Machinery, 2022, pp. 1–10

2022

Cited alongside, same era.

——, “Introducing ChatGPT,” 11 2022. [Online]. Available: https://openai.com/blog/chatgpt

2022

Cited alongside, same era.

T. Kojima, S. S. Gu, M. Reid, Y. Matsuo, and Y. Iwasawa, “Large language models are zero-shot reasoners,” in Advances in Neural Information Processing Systems , vol. 35, 5 2022, pp. 22 199–22 213

2022

Cited alongside, same era.

J. Wei, X. Wang, D. Schuurmans, M. Bosma, B. Ichter, F. Xia, E. Chi, Q. Le, and D. Zhou, “Chain-of-thought prompting elicits reasoning in large language models,” arXiv , 1 2022

2022

Cited alongside, same era.

——, “GPT-4,” 3 2023. [Online]. Available: https://openai.com/research/gpt-4

2023

Later among the works it cites.

S. Pichai and D. Hassabis, “Introducing gemini: Google’s most capable ai model yet,” 2023. [Online]. Available: https://blog.google/technology/ai/google-gemini-ai/

2023

Later among the works it cites.

Gemini-Team, “Gemini: A family of highly capable multimodal models,” arXiv , 12 2023

2023

Later among the works it cites.

Meta, “Meta and microsoft introduce the next generation of llama | meta,” 2023. [Online]. Available: https://about.meta.com/news/2023/07/llama-2/

2023

Later among the works it cites.

Z. Sun, X. Wang, Y. Tay, Y. Yang, and D. Zhou, “Recitation-augmented language models,” in The Eleventh International Conference on Learning Representations , 10 2023

2023

Later among the works it cites.