Dataset Groups Activity Stream 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). BibTex: @dataset{Ling_Yang_and_Zhaochen_Yu_and_Tianjun_Zhang_and_Shiyi_Cao_and_Minkai_Xu_and_Wentao_Zhang_and_Joseph_E_Gonzalez_and_Bin_Cui_2024, abstract = {Buffer of Thoughts is a novel and versatile thought-augmented reasoning approach for enhancing accuracy, efficiency and robustness of large language models (LLMs).}, author = {Ling Yang and Zhaochen Yu and Tianjun Zhang and Shiyi Cao and Minkai Xu and Wentao Zhang and Joseph E. Gonzalez and Bin Cui}, doi = {10.57702/6z041tgi}, institution = {No Organization}, keyword = {'accuracy', 'efficiency', 'large language models', 'robustness', 'thought-augmented reasoning'}, month = {dec}, publisher = {TIB}, title = {Buffer of Thoughts}, url = {https://service.tib.eu/ldmservice/dataset/buffer-of-thoughts}, year = {2024} }
