8 citations · 19 across the 6 of their papers we have counts for
6 papers
JETHICS: Japanese Ethics Understanding Evaluation Dataset
Masashi Takeshita, Rafal Rzepka
In this work, we propose JETHICS, a Japanese dataset for evaluating ethics understanding of AI models. JETHICS contains 78K examples and is built by following the construction meth…
Speciesism in Natural Language Processing Research
Masashi Takeshita, Rafal Rzepka
Natural Language Processing (NLP) research on AI Safety and social bias in AI has focused on safety for humans and social bias against human minorities. However, some AI ethicists…
LLM-jp: A Cross-organizational Project for the Research and Development of Fully Open Japanese LLMs
LLM-jp, :, Akiko Aizawa +80
This paper introduces LLM-jp, a cross-organizational project for the research and development of Japanese large language models (LLMs). LLM-jp aims to develop open-source and stron…
JBBQ: Japanese Bias Benchmark for Analyzing Social Biases in Large Language Models
Hitomi Yanaka, Namgi Han, Ryoma Kumon +5
With the development of large language models (LLMs), social biases in these LLMs have become a pressing issue. Although there are various benchmarks for social biases across langu…
Towards Theory-based Moral AI: Moral AI with Aggregating Models Based on Normative Ethical Theory
Masashi Takeshita, Rzepka Rafal, Kenji Araki
Moral AI has been studied in the fields of philosophy and artificial intelligence. Although most existing studies are only theoretical, recent developments in AI have made it incre…
Speciesist Language and Nonhuman Animal Bias in English Masked Language Models
Masashi Takeshita, Rafal Rzepka, Kenji Araki
Various existing studies have analyzed what social biases are inherited by NLP models. These biases may directly or indirectly harm people, therefore previous studies have focused…