SlideLab: Audience-Centered Scientific Slide Generation and Evaluation

arXiv:2609.30294v1 Announce Type: cross 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.

Related

• Science sandboxes measure the scientific capability of AI agents
• A Survey on MLLM-based Visually Rich Document Understanding: Methods, Challenges, and Emerging Trends
• HiLSVA: Design and Evaluation of a Human-in-the-Loop Agentic System for Scientific Visualization

Source: arXiv cs.AI | 2026-09-28