[Submitted on 13 Sep 2026]
Title:SlideLab: Audience-Centered Scientific Slide Generation and Evaluation
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Abstract:Scientific presentations are more than summaries of research papers. They need to present the work in a coherent sequence, explain the main ideas clearly, and help the audience follow the presentation. We present SlideLab, a training-free multi-agent framework for generating scientific presentations from research papers. SlideLab first plans the presentation narrative, then builds and iteratively refines a shared slide deck using agents for content planning, visual generation, layout refinement, and grounding verification. In a blind human preference study, SlideLab was preferred over both open-source and commercial systems on 77% of papers while using roughly 4 times fewer inference tokens than the strongest open-source baseline. We also introduce ConfArena, an audience-oriented evaluation framework that simulates a conference room and assesses presentations slide by slide. ConfArena matches human system rankings and detects injected presentation problems, including falsified numbers, degraded figures, dropped slides, and shuffled slide order.
Comments: V1
Subjects:
Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2609.30294 [cs.CL]
(or arXiv:2609.30294v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2609.30294
arXiv-issued DOI via DataCite
Submission history
From: Vidushee Vats [view email] [v1] Sun, 13 Sep 2026 10:39:04 UTC (11,019 KB)
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