Papers by Yongxue Shan

2 papers
Reasoning with Ontology Graph: Toward Type-Constrained Knowledge Graph Question Answering (2026.acl-long)

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Challenge: Existing knowledge graph question answering methods rely on LLM-induced type systems with inconsistent granularity or perform multi-hop reasoning without explicit target-type constraints.
Approach: They propose a type-constrained knowledge graph question answering framework that reasons over a relation-centric ontology graph.
Outcome: The proposed framework achieves state-of-the-art and produces ontology-grounded reasoning chains with substantial Hit@1 gains.
EffiQA: Efficient Question-Answering with Strategic Multi-Model Collaboration on Knowledge Graphs (2025.coling-main)

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Challenge: Existing approaches that integrate LLMs and KGs either underutilize the reasoning abilities of LLM or suffer from prohibitive computational costs due to tight coupling.
Approach: They propose a framework that can strike a balance between performance and efficiency via an iterative paradigm.
Outcome: The proposed framework can strike a balance between performance and efficiency via an iterative paradigm.

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