# SlideTailor: Personalized Presentation Slide Generation for Scientific Papers

arXiv: https://arxiv.org/abs/2512.20292 · HTML: https://mlsanity.com/paper/2512.20292/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- Builds on 19 of its 38 references that are in the map.
- First posted on arXiv 23 Dec 2025.

## Builds on (most cited first, 19 of 19)

- [PPTAgent: Generating and Evaluating Presentations Beyond Text-to-Slides](https://mlsanity.com/paper/2501.03936/) (2025)
- [DOC2PPT: Automatic Presentation Slides Generation from Scientific Documents](https://mlsanity.com/paper/2101.11796/) (2021)
- [AutoPresent: Designing Structured Visuals from Scratch](https://mlsanity.com/paper/2501.00912/) (2025)
- [Paper2Poster: Towards Multimodal Poster Automation from Scientific Papers](https://mlsanity.com/paper/2505.21497/) (2025)
- [D2S: Document-to-Slide Generation Via Query-Based Text Summarization](https://mlsanity.com/paper/2105.03664/) (2021)
- [MegaTTS 3: Sparse Alignment Enhanced Latent Diffusion Transformer for Zero-Shot Speech Synthesis](https://mlsanity.com/paper/2502.18924/) (2025)
- [MEMO: Memory-Guided Diffusion for Expressive Talking Video Generation](https://mlsanity.com/paper/2412.04448/) (2024)
- [Paper2Video: Automatic Video Generation from Scientific Papers](https://mlsanity.com/paper/2510.05096/) (2025)
- [PresentAgent: Multimodal Agent for Presentation Video Generation](https://mlsanity.com/paper/2507.04036/) (2025)
- [Enhancing Presentation Slide Generation by LLMs with a Multi-Staged End-to-End Approach](https://mlsanity.com/paper/2406.06556/) (2024)
- [SciDoc2Diagrammer-MAF: Towards Generation of Scientific Diagrams from Documents guided by Multi-Aspect Feedback Refinement](https://mlsanity.com/paper/2409.19242/) (2024)
- [Neural Content Extraction for Poster Generation of Scientific Papers](https://mlsanity.com/paper/2112.08550/) (2021)
- [Towards Personalized Review Summarization by Modeling Historical Reviews from Customer and Product Separately](https://mlsanity.com/paper/2301.11682/) (2023)
- [LMGQS: A Large-scale Dataset for Query-focused Summarization](https://mlsanity.com/paper/2305.13086/) (2023)
- [Just What You Desire: Constrained Timeline Summarization with Self-Reflection for Enhanced Relevance](https://mlsanity.com/paper/2412.17408/) (2024)
- [Knowledge-Centric Templatic Views of Documents](https://mlsanity.com/paper/2401.06945/) (2024)
- [SumRecom: A Personalized Summarization Approach by Learning from Users' Feedback](https://mlsanity.com/paper/2408.07294/) (2024)
- [Textual-to-Visual Iterative Self-Verification for Slide Generation](https://mlsanity.com/paper/2502.15412/) (2025)
- [IDEAL: Leveraging Infinite and Dynamic Characterizations of Large Language Models for Query-focused Summarization](https://mlsanity.com/paper/2407.10486/) (2024)

## Built on by (most cited first, 13 of 13)

- [DeepPresenter: Environment-Grounded Reflection for Agentic Presentation Generation](https://mlsanity.com/paper/2602.22839/) (2026)
- [AI for Auto-Research: Roadmap & User Guide](https://mlsanity.com/paper/2605.18661/) (2026)
- [SciFig: Towards Automating Editable Figure Generation for Scientific Papers](https://mlsanity.com/paper/2601.04390/) (2026)
- [EvoDiagram: Agentic Editable Diagram Creation via Design Expertise Evolution](https://mlsanity.com/paper/2604.09568/) (2026)
- [MemSlides: A Hierarchical Memory Driven Agent Framework for Personalized Slide Generation with Multi-turn Local Revision](https://mlsanity.com/paper/2606.17162/) (2026)
- [SeaSlides: Semantic Abstraction Layer for Agentic Slide Generation](https://mlsanity.com/paper/2608.03298/) (2026)
- [Agentic Visual Generation: From Generative Models to Agentic Control](https://mlsanity.com/paper/2609.06758/) (2026)
- [X+Slides: Benchmarking Audience-Conditioned Slide Generation](https://mlsanity.com/paper/2606.19256/) (2026)
- [Personalization as Inverse Planning: Learning Latent Design Intents for Agentic Slide Generation via Structural Denoising](https://mlsanity.com/paper/2607.00407/) (2026)
- [ReDeck: Step-Level Render-Grounded Refinement for Document-to-Slide Generation](https://mlsanity.com/paper/2609.00194/) (2026)
- [ConvDeck: Conversational Paper-to-Slide Generation via Stage-Specific User Feedback](https://mlsanity.com/paper/2609.00226/) (2026)
- [SLIDEFORGE: An LLM Agent for Controllable Editing of Slides as Structured Artifacts](https://mlsanity.com/paper/2609.03109/) (2026)
- [InfoAgent: Traceable Generation and Repair of Evidence-Grounded Infographics](https://mlsanity.com/paper/2609.39380/) (2026)

## Abstract (arXiv)

Automatic presentation slide generation can greatly streamline content creation. However, since preferences of each user may vary, existing under-specified formulations often lead to suboptimal results that fail to align with individual user needs. We introduce a novel task that conditions paper-to-slides generation on user-specified preferences. We propose a human behavior-inspired agentic framework, SlideTailor, that progressively generates editable slides in a user-aligned manner. Instead of requiring users to write their preferences in detailed textual form, our system only asks for a paper-slides example pair and a visual template - natural and easy-to-provide artifacts that implicitly encode rich user preferences across content and visual style. Despite the implicit and unlabeled nature of these inputs, our framework effectively distills and generalizes the preferences to guide customized slide generation. We also introduce a novel chain-of-speech mechanism to align slide content with planned oral narration. Such a design significantly enhances the quality of generated slides and enables downstream applications like video presentations. To support this new task, we construct a benchmark dataset that captures diverse user preferences, with carefully designed interpretable metrics for robust evaluation. Extensive experiments demonstrate the effectiveness of our framework.