YOMI-Bench: A Benchmark for Evaluating Kanji Reading and Phonological Understanding of LLMs for Japanese
arXiv:2607.00664v1 Announce Type: new Abstract: 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 ou
The proliferation of Large Language Models (LLMs) and their increasing application in global contexts necessitates more sophisticated evaluation benchmarks, particularly for linguistically complex languages like Japanese, where existing models exhibit known weaknesses.
This benchmark highlights fundamental limitations in current LLM architectures regarding deep linguistic understanding for non-English languages, exposing critical areas for research and development to achieve truly multilingual AI.
The YOMI-Bench provides a standardized tool to accurately measure and compare the phonological and kanji reading comprehension of LLMs in Japanese, enabling targeted improvements and fostering competition in this specific domain.
- · Japanese AI research community
- · Developers of multilingual LLMs
- · Japanese language services leveraging AI
- · LLMs with poor Japanese language understanding
- · Companies relying on superficial multilingual AI solutions
YOMI-Bench drives immediate research focus on improving kanji reading and phonological understanding in LLMs for Japanese.
Improved Japanese language capabilities in LLMs could lead to more robust and culturally nuanced AI products and services for the Japanese market.
Success in addressing Japanese linguistic complexities may inform and accelerate the development of advanced multilingual LLMs for other challenging languages, leading to a broader global adoption of AI.
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