SlideTailor: Personalized Presentation Slide Generation for Scientific Papers
Wenzheng Zeng, Mingyu Ouyang, Langyuan Cui, Hwee Tou Ng

TL;DR
SlideTailor is a novel system that personalizes scientific presentation slides based on minimal user input, effectively aligning content and style through a behavior-inspired framework and a new benchmark dataset.
Contribution
We introduce a new task for personalized slide generation conditioned on implicit user preferences, along with a novel framework and a benchmark dataset for evaluation.
Findings
Effective personalization of slides using minimal inputs
Improved slide quality and alignment with user preferences
Versatile application to video presentations and oral narration
Abstract
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…
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Code & Models
Videos
Taxonomy
TopicsVideo Analysis and Summarization · Multimodal Machine Learning Applications · Multimedia Communication and Technology
