Papers by Hisada Shohei
Single-Agent Generation Surpasses Multi-Agent Systems in Semantic Diversity (2026.findings-acl)
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| Challenge: | Multi-Agent Systems (MAS) are used to improve reasoning diversity and robustness by simulating interactions among agents with distinct roles. |
| Approach: | They find that a Multi-Output strategy produces the highest diversity without degrading logical validity. |
| Outcome: | The proposed approach outperforms multi-agent systems in semantic diversity . the results point to a more efficient and effective way to expand diversity - the authors say . |
Annotation-Scheme Reconstruction for “Fake News” and Japanese Fake News Dataset (2022.lrec-1)
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| Challenge: | Contemporary research focuses on the factuality aspect of the news, but this aspect alone is insufficient to explain “fake news.” |
| Approach: | They propose to use Japanese fake news datasets to classify whether news content is false . they propose to do this by using existing fake news data to investigate fake news . |
| Outcome: | The proposed scheme will provide an in-depth understanding of fake news in Japan and other languages. |
Exploring LLM Annotation for Adaptation of Clinical Information Extraction Models under Data-sharing Restrictions (2025.findings-acl)
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| Challenge: | In-hospital text data often contains valuable clinical information, yet fine-tuned small language models (SLMs) for information extraction remain challenging due to differences in formatting and vocabulary across institutions. |
| Approach: | They leverage large language models to annotate the target domain data for adaptation . they use in-hospital text data to extract clinical information . |
| Outcome: | The proposed model outperforms manual annotation on four clinical information extraction tasks with a larger number of annotated data. |