mlsanityData to 13 Oct 2026

YOMI-Bench: A Benchmark for Evaluating Kanji Reading and Phonological Understanding of LLMs for Japanese

arXiv 2607.00664 ↗First posted 1 Jul 2026cs.CLcited by 1

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Abstract (arXiv)

We propose YOMI-Bench, a benchmark for evaluating kanji reading and phonological understanding of large language models (LLMs) for Japanese. In Japanese, a single kanji character often has multiple possible readings, making it difficult to infer the correct reading from surface-level text alone. Due to these linguistic characteristics, it is empirically known that LLMs exhibit low performance in kanji reading for Japanese. The proposed YOMI-Bench consists of four tasks specifically designed to evaluate kanji reading performance in Japanese. In our evaluation using YOMI-Bench, we assessed one multilingual open LLM, four Japanese-specific open LLMs, and five commercial LLMs. As a result, we found that even Japanese-specific models show low performance, and that commercial models also perform poorly on generation tasks that require consideration of kanji readings.

Key facts. Cited by 1 paper in the map (data through 13 Oct 2026). Builds on 6 of its 13 references that are in the map. First posted on arXiv 1 Jul 2026.

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6 of 13 references.

References · 6

  1. 2023Large Language Models Are Not Robust Multiple Choice Selectorscited by 470
  2. 2018The CoNLL--SIGMORPHON 2018 Shared Task: Universal Morphological Reinflectioncited by 41
  3. 2024LLMs May Perform MCQA by Selecting the Least Incorrect Optioncited by 32
  4. 2021DeepRapper: Neural Rap Generation with Rhyme and Rhythm Modelingcited by 24
  5. 2024Multilingual Large Language Models: A Systematic Surveycited by 18
  6. 2024Why We Build Local Large Language Models: An Observational Analysis from 35 Japanese and Multilingual LLMscited by 4

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