Papers by Sukhwa Hong

1 papers
StrucSum: Graph-Structured Reasoning for Long Document Extractive Summarization with LLMs (2026.findings-eacl)

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Challenge: Large language models (LLMs) have shown strong performance in zero-shot summarization, but struggle to model document structure and identify salient information in long texts.
Approach: They propose a training-free prompting framework that injects structural signals into prompts via sentence-level graph structures.
Outcome: The proposed framework improves summary quality and factual consistency over baselines and vanilla prompting.

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