Papers by Jinwang Wu

2 papers
An Investigation of LLMs’ Inefficacy in Understanding Converse Relations (2023.emnlp-main)

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Challenge: Existing benchmarks for Large Language Models (LLMs) follow the data distribution of pre-training data.
Approach: They propose a benchmark ConvRe focusing on converse relations which contains 17 relations and 1240 triples extracted from popular knowledge graph completion datasets.
Outcome: The proposed benchmark focuses on converse relations, which contains 17 relations and 1240 triples extracted from popular knowledge graph completion datasets.
CMoralEval: A Moral Evaluation Benchmark for Chinese Large Language Models (2024.findings-acl)

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Challenge: Recent years have witnessed remarkable progress achieved by large language models in both natural language understanding and generation.
Approach: They propose a large benchmark CMoralEval for moral evaluation of Chinese LLMs . they use a Chinese TV program discussing Chinese moral norms and Chinese moral anomies based on various sources .
Outcome: The proposed dataset is characterized by diversity and authenticity.

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