CAF-Gen: A Multi-Agent System for Enriching Argumentation Structures
Formalizing complex reasoning from natural text is one of the central challenges in computational linguistics. It requires systems to understand not just keywords but also the context and complex reasoning embedded in a text. Current Argument Mining (AM) techniques identify basic claims and premises, yet they often struggle to capture the richer structural information required by advanced schemas such as the Carneades Argumentation Framework (CAF), which incorporates features such as premise types, proof standards, and argument schemes. We address this limitation by introducing CAF-Gen, an automated multi-agent framework designed to enrich shallow argument structures into CAF-compliant ar...
| Authors | Jakub Bąba, Jarosław A. Chudziak |
|---|---|
| Primary category | cs.CL |
| Published | 4 June 2026 |
| Last updated at source | 14 June 2026 |
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