Papers by Taisei Yamamoto

2 papers
Bias Mitigation or Cultural Commonsense? Evaluating LLMs with a Japanese Dataset (2025.emnlp-main)

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Challenge: Recent studies have demonstrated that large language models exhibit social biases . however, debiasing methods may degrade the capabilities of LLMs if they are not properly evaluated .
Approach: They propose a Japanese benchmark to evaluate social biases and cultural commonsense in large language models in a unified format.
Outcome: The proposed method degrades the performance of the LLMs on the cultural commonsense task by 75%.
Evaluation of Multilingual Ability to Use Spatial Deictic Expressions in Vision-Language Models (2026.acl-srw)

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Challenge: Existing studies have focused on the ability of vision-language models to utilize spatial deictic expressions, which depend on the situation of utterance.
Approach: They develop a benchmark to evaluate the multilingual ability of VLMs to use spatial deictic expressions in four languages.
Outcome: The proposed models use demonstratives in a different manner from humans, particularly in selecting demonstrative based on distance from the object.

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