Narrative-Driven Paper-to-Slide Generation via ArcDeck

We introduce ArcDeck, a multi-agent framework that for-mulates paper-to-slide generation as a structured narrative reconstruc-tion task. Unlike existing methods that directly summarize raw text intoslides, ArcDeck explicitly models the source paper’s logical flow. It firstparses the input to construct a discourse tree and establish a global com-mitment document, ensuring the high-level intent is preserved. Thesestructural priors then guide an iterative multi-agent refinement process,where specialized agents iteratively critique and revise the presentationoutline before rendering the final visual layouts and designs. To evaluateour approach, we also introduce ArcBench, a newly curated benchmarkof academic paper-slide pairs. Experimental results demonstrate that ex-plicit discourse modeling, combined with role-specific agent coordination,significantly improves the narrative flow and logical coherence of the gen-erated presentations. The ArcDeck codebase and ArcBench benchmarkare available on our project webpage.