Papers by Chengyi Ju

1 papers
Benchmarking Multi-National Value Alignment for Large Language Models (2025.findings-acl)

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Challenge: Existing studies on large language models focus on ethical reviews, failing to capture the diversity of national values.
Approach: They propose a national value extraction pipeline to efficiently construct value assessment datasets and a model-based model with instruction tagging to process raw data sources.
Outcome: The proposed benchmark evaluates the alignment of LLMs with the values of five major nations: China, the United States, the UK, France, and Germany.

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