Papers by Chengwen Qi

    1 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.

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