Papers by Qingchao Kong

2 papers
Dual Complex Number Knowledge Graph Embeddings (2024.lrec-main)

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Challenge: Existing knowledge graph embedding methods fail to model non-commutative composition patterns . extending to such sophisticated spaces increases the amount of parameters, which greatly reduces the parameter efficiency.
Approach: They propose a new knowledge graph embedding method that maps entities to the dual complex number space and represents relations as rotations in 2D space via dual complex multiplication.
Outcome: Experiments on multiple benchmark knowledge graphs show that the proposed method improves link prediction and path query answering.
Perspective-driven Preference Optimization with Entropy Maximization for Diverse Argument Generation (2025.findings-emnlp)

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Challenge: Argument generation with diverse perspectives is essential for fostering balanced discourse and mitigating bias.
Approach: They propose a Perspective-aware Preference Optimization with Entropy Maximization framework for diverse argument generation.
Outcome: The proposed framework enhances perspective diversity through preference optimization based on the constructed preference dataset .

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