Self-Consistency Improves Chain of Thought Reasoning in Language Models
Wang et al., 2023, Self-Consistency Improves Chain of Thought Reasoning in Language Models (The Eleventh International Conference on Learning Representations (ICLR 2023))
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5 Conclusion and Discussion
- What are self-consistency’s main limitations?It multiplies inference cost by the number of sampled paths, and models still sometimes produce incorrect or nonsensical reasoning paths even when the voted answer is right, so rationales need better grounding.
- Wang et al., 2023, Self-Consistency Improves Chain of Thought Reasoning in Language Models (The Eleventh International Conference on Learning Representations (ICLR 2023)), §5
Source
- Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed H. Chi, Sharan Narang, Aakanksha Chowdhery and Denny Zhou. 2023. Self-Consistency Improves Chain of Thought Reasoning in Language Models. In The Eleventh International Conference on Learning Representations (ICLR 2023). https://arxiv.org/abs/2203.11171