Papers by Rei Minamoto
Detecting Sensitive Personal Information in Japanese Pre-Training Corpora for Large Language Models (2026.findings-acl)
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| Challenge: | Large-scale pre-training corpora are essential for large language models, but if such content remains unfiltered, there is a risk that LLMs may memorize it and leak it through their outputs. |
| Approach: | They construct a Japanese text corpora dataset and train machine learning models to detect SCPI in text. |
| Outcome: | The proposed classifier can detect information related to SCPI in Japanese text. |
Constructing a Japanese Verdict Prediction Dataset for Fact-Checking of LLM-Generated Texts (2026.acl-srw)
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Miwa Masano, Hirokazu Kiyomaru, Atsushi Keyaki, Kaito Horio, Rei Minamoto, Ribeka Keyaki, Kouta Nakayama, Hideyuki Tachibana, Daisuke Kawahara
| Challenge: | Text generated by Large Language Models (LLMs) may contain plausible but incorrect information known as hallucinations. |
| Approach: | They extend the label set for verdict prediction to capture claim-evidence relationships humans would commonly interpret as supported or refuted. |
| Outcome: | The proposed system improves F1 by 4 percentage points compared to baseline. |