Papers by Himanshu Chaudhary

1 papers
GRAFF: GRaph-Augmented Fine-grained Fusion for Large Language Models (2026.findings-eacl)

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Challenge: Existing methods to integrate graphs into LLMs compress the graph's structural information into a single token, restricting their ability to capture deep semantic and structural information.
Approach: They propose a method that integrates fine-grained node-level structural information with corresponding text entities to LLMs via a lightweight, structure adapter module.
Outcome: The proposed method outperforms baseline models in graph-based question answering by 10.24%.

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