Papers by Yeonsu Kwon

3 papers
KG-GPT: A General Framework for Reasoning on Knowledge Graphs Using Large Language Models (2023.findings-emnlp)

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Challenge: Using large language models for complex reasoning tasks on knowledge graphs remains unexplored.
Approach: They propose a multi-purpose framework leveraging large language models for complex reasoning tasks on knowledge graphs.
Outcome: The proposed framework outperforms fully-supervised models in KG-based fact verification and KGQA benchmarks.
FactKG: Fact Verification via Reasoning on Knowledge Graphs (2023.acl-long)

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Challenge: knowledge graphs (KGs) have not been fully utilized as a knowledge source for fact verification.
Approach: They propose a dataset to enable the community to better use knowledge graphs . they propose 108k natural language claims with five types of reasoning .
Outcome: The proposed dataset consists of 108k natural language claims with five types of reasoning . authors believe the proposed method can advance reliability and practicality .
Open-WikiTable : Dataset for Open Domain Question Answering with Complex Reasoning over Table (2023.findings-acl)

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Challenge: Open-WikiTable is the first open domain question answering dataset that requires complex reasoning over tables.
Approach: They propose to use open-domain question answering over tables to extract questions from tables.
Outcome: The dataset is publicly available. it is built upon WikiSQL and WikiTableQuestions.

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