SeaSlides: Semantic Abstraction Layer for Agentic Slide Generation
On the map: LLM agents and tool use → Multimodal and embodied agents
Abstract (arXiv)
Agentic presentation generation must preserve source content, maintain coherent visual design, render specialized objects, and produce usable artifacts. Existing systems meet only part of this requirement: templates preserve regularity but restrict adaptation, whereas free-form HTML or SVG gives models flexibility at the cost of low-level rendering decisions. This mismatch makes long technical decks brittle, especially when slides contain formulas, code, or data graphics. We present SeaSlides, an agentic slide-generation framework built around a semantic abstraction layer. Rather than authoring coordinates, inline styles, or raw SVG geometry, the model writes structured slide content through reusable components and capability modules, while templates own layout, style, and rendering. We instantiate this principle separately in HTML and Typst: SeaSlides-HTML uses template-defined DOM components, whereas SeaSlides-Typst uses template functions and package-backed modules. Capability modules route equations, code, and charts to dedicated renderers, and three feedback stages localize build errors, project-constraint violations, and visual defects before export. The two systems retain backend-specific syntax and contracts while sharing the same authoring boundary. For evaluation, we combine the 128-task UltraPresent validation setting with SeaSlidesBench-Rich, a new 32-task benchmark stressing mathematics, code, pseudocode, tables, charts, and diagrams. Across four generation models, both SeaSlides backends produce more readable, content-oriented source than SVG-heavy generation. A SeaSlides backend attains the highest rich-content macro-average under three of the four models while maintaining competitive overall qualitative performance. These results support semantic abstraction as a practical authoring principle across presentation backends.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in Multimodal and embodied agents, one of 16 directions in LLM agents and tool use. Builds on 24 of its 43 references that are in the map. First posted on arXiv 4 Aug 2026.
Builds on
24 of 43 references.
Closest ancestors · 3
Same direction, newest first
- 2026DeepPresenter: Environment-Grounded Reflection for Agentic Presentation Generation26 Feb
- 2025PreGenie: An Agentic Framework for High-quality Visual Presentation Generation27 May
- 2024MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization18 Feb
Other references · 21
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- 2023DINOv2: Learning Robust Visual Features without Supervisioncited by 7,974
- 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,442
- 2023G-Eval: NLG Evaluation using GPT-4 with Better Human Alignmentcited by 2,276
- 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,988
- 2023CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquingcited by 783
- 2022The Vendi Score: A Diversity Evaluation Metric for Machine Learningcited by 311
- 2024Design2Code: Benchmarking Multimodal Code Generation for Automated Front-End Engineeringcited by 152
- 2025PPTAgent: Generating and Evaluating Presentations Beyond Text-to-Slidescited by 86
- 2021DOC2PPT: Automatic Presentation Slides Generation from Scientific Documentscited by 70
- 2025AutoPresent: Designing Structured Visuals from Scratchcited by 68
9 more
- 2021D2S: Document-to-Slide Generation Via Query-Based Text Summarizationcited by 50
- 2025SlideGen: Collaborative Multimodal Agents for Scientific Slide Generationcited by 25
- 2025Auto-Slides: An Interactive Multi-Agent System for Creating and Customizing Research Presentationscited by 19
- 2025PPTBench: Towards Holistic Evaluation of Large Language Models for PowerPoint Layout and Design Understandingcited by 14
- 2026PresentBench: A Fine-Grained Rubric-Based Benchmark for Slide Generationcited by 14
- 2025Presenting a Paper is an Art: Self-Improvement Aesthetic Agents for Academic Presentationscited by 13
- 2025SlideTailor: Personalized Presentation Slide Generation for Scientific Paperscited by 13
- 2025Talk to Your Slides: High-Efficiency Slide Editing via Language-Driven Structured Data Manipulationcited by 11
- 2016Building an Interpretable Recommender via Loss-Preserving Transformationcited by 1
Built on by
Citing papers per year: 2026: 1.
1 paper.
Similar, not cited
Close in wording, no citation either way
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