Does Self-Consistency Improve the Recall of Encyclopedic Knowledge?

Sho Hoshino, Ukyo Honda, Peinan Zhang
4/21/2026
cs.CL

No confident code implementation found for this paper.

Abstract

While self-consistency is known to improve performance on symbolic reasoning, its effect on the recall of encyclopedic knowledge is unclear due to a lack of targeted evaluation grounds. To address this, we establish such a knowledge recall split for the popular MMLU benchmark by applying a data-driven heuristic from prior work. We validate this split by showing that the performance patterns on the symbolic reasoning and knowledge recall subsets mirror those of GSM8K and MedMCQA, respectively. Using this solid ground, we find that self-consistency consistently improves performance across both symbolic reasoning and knowledge recall, even though its underlying CoT prompting is primarily effective for symbolic reasoning. As a result, we achieve an 89\% accuracy on MMLU, the best performance to date with the use of GPT-4o.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{hoshino2026does,
  title  = {Does Self-Consistency Improve the Recall of Encyclopedic Knowledge?},
  author = {Sho Hoshino and Ukyo Honda and Peinan Zhang},
  year   = {2026},
  eprint = {2604.19395},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2604.19395v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2604.19395.svg)](https://codeofpaper.com/paper/2604.19395)

Discussion