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20172026
most citedDiscovering Options for Exploration by Minimizing Cover Time

11 citations · 19 across the 22 of their papers we have counts for

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cs.CL2026

JOR-Bench: Japanese Operations Research Benchmarks for Large Language Models

Yuu Jinnai

We present JOR-Bench, a collection of five Japanese-language benchmarks for evaluating the ability of large language models (LLMs) to formulate and solve operations research (OR) p…

cs.CL2026

Cost of Reasoning in non-English Languages: A Case Study on Japanese

Yuu Jinnai

Reasoning Language Models (RLMs) achieve their strongest performance when they reason in English, the language for which reasoning-oriented training data is most abundant. However,…

cs.CL2026

CAT-Translate: Building Compact Open-Source Models for Japanese-English Translation

Yuu Jinnai

Nowadays, large multilingual translation models demonstrate impressive translation capabilities in the machine translation benchmarks. This raises a practical question to the devel…

cs.CL2025

Re-evaluating Minimum Bayes Risk Decoding for Automatic Speech Recognition

Yuu Jinnai

Recent work has shown that sample-based Minimum Bayes Risk (MBR) decoding outperforms beam search in text-to-text generation tasks, such as machine translation, text summarization,…

cs.CL2025

Do Large Language Models Know Folktales? A Case Study of Yokai in Japanese Folktales

Ayuto Tsutsumi, Yuu Jinnai

Although Large Language Models (LLMs) have demonstrated strong language understanding and generation abilities across various languages, their cultural knowledge is often limited t…

cs.CL2025

Document-Level Text Generation with Minimum Bayes Risk Decoding using Optimal Transport

Yuu Jinnai

Document-level text generation tasks are known to be more difficult than sentence-level text generation tasks as they require the understanding of longer context to generate high-q…