Papers by Yaru Wang

2 papers
Flames: Benchmarking Value Alignment of LLMs in Chinese (2024.naacl-long)

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Challenge: Existing benchmarks for large language models (LLMs) do not accurately uncover safety vulnerabilities in LLMs.
Approach: They propose a value alignment benchmark called Flames that encompasses both harmlessness principles and a unique morality dimension that integrates specific Chinese values such as harmony.
Outcome: The proposed model performs poorly on Flames, particularly in safety and fairness dimensions.
SocialEval: Evaluating Social Intelligence of Large Language Models (2025.acl-long)

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Challenge: Existing work on LLMs does not address their social intelligence (SI) and their discrepancy with humans.
Approach: They propose a script-based bilingual SI benchmark that integrates outcome-oriented goal achievement evaluation and process-oriented interpersonal ability evaluation by manually crafting narrative scripts.
Outcome: The proposed model is based on a script-based bilingual evaluation paradigm that integrates outcome- and process-oriented evaluation by manually crafting narrative scripts.

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