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Buffer of Thoughts

Buffer of Thoughts is a novel and versatile thought-augmented reasoning approach for enhancing accuracy, efficiency and robustness of large language models (LLMs).

Data and Resources

Cite this as

Ling Yang, Zhaochen Yu, Tianjun Zhang, Shiyi Cao, Minkai Xu, Wentao Zhang, Joseph E. Gonzalez, Bin Cui (2024). Dataset: Buffer of Thoughts. https://doi.org/10.57702/6z041tgi

DOI retrieved: December 16, 2024

Additional Info

Field Value
Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2406.04271
Author Ling Yang
More Authors
Zhaochen Yu
Tianjun Zhang
Shiyi Cao
Minkai Xu
Wentao Zhang
Joseph E. Gonzalez
Bin Cui
Homepage https://github.com/YangLing0818/buffer-of-thought-llm