January 1, 2023Open Access

Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them

Puntos clave

Los puntos clave no están disponibles para este artículo en este momento.

Resumen

Mirac Suzgun, Nathan Scales, Nathanael Schärli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc Le, Ed Chi, Denny Zhou, Jason Wei. Findings of the Association for Computational Linguistics: ACL 2023. 2023.

Preguntar a la IA

Me gusta

Guardar

Ver artículo completo

Cite This Study

Süzgün et al. (Sun,) studied this question.

synapsesocial.com/papers/69b03cbc98a0803b6cb32c43 https://doi.org/https://doi.org/10.18653/v1/2023.findings-acl.824

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Can language models learn from explanations in context?2022 · 125 citations
2True Few-Shot Learning with Language Models2021 · 194 citations
3Show Your Work: Scratchpads for Intermediate Computation with Language\n Models2021 · 131 citations
4On the Machine Learning of Ethical Judgments from Natural Language2022 · 30 citations
5Text and Patterns: For Effective Chain of Thought, It Takes Two to Tango2022 · 22 citations

Preguntar a la IA

Me gusta

Guardar

Ver artículo completo