Talk to Your Slides: Language-Driven Agents for Efficient Slide Editing

ACL ARR 2025 May Submission1326 Authors

Abstract:

Editing presentation slides remains one of the most common and time-consuming tasks faced by millions of users daily, despite significant advances in automated slide generation.
Existing approaches have successfully demonstrated slide editing via graphic user interface (GUI)-based agents, offering intuitive visual control. However, such methods often suffer from high computational cost and latency.
In this paper, we propose Talk-to-Your-Slides, an LLM-powered agent designed to edit slides %in active PowerPoint sessions
by leveraging structured information about slide objects rather than relying on image modality.
The key insight of our work is designing the editing process with distinct high-level and low-level layers to facilitate interaction between user commands and slide objects.
By providing direct access to application objects rather than screen pixels, our system enables 34.02% faster processing, 34.76% better instruction fidelity, and 87.42% cheaper operation than baselines.
To evaluate slide editing capabilities, we introduce TSBench, a human-annotated dataset comprising 379 diverse editing instructions paired with corresponding slide variations in four categories.
Our code, benchmark and demos are available at https://anonymous.4open.science/r/Talk-to-Your-Slides-0F4C.

Paper Type: Long

Research Area: NLP Applications

Research Area Keywords: NLP Applications, Resources and Evaluation, Language Modeling

Contribution Types: NLP engineering experiment, Data resources

Languages Studied: English

Keywords: Large language models, slide editing, code generation

Submission Number: 1326