Chen Tang

Improving End-to-End Argument Mining with LLMs via Multi-Candidate Reranking and Bounded Repair

End-to-end Argument Mining (AM) aims to extract structured argument graphs directly from raw text by jointly identifying components and their rhetorical relations. Large Language Models (LLMs) have shown promise for this complex task by formulating it as direct text-to-graph generation. However, since most current LLM-...