Papers with academic QA

1 papers
HetGCoT: Heterogeneous Graph-Enhanced Chain-of-Thought LLM Reasoning for Academic Question Answering (2025.findings-emnlp)

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Challenge: graph neural networks capture structured graph information, but lack integration at the reasoning level.
Approach: They propose a framework that leverages graph structural information to reason interpretable academic QA results.
Outcome: The proposed framework outperforms sota baselines on OpenAlex and DBLP datasets.

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