arXiv:2606.19256v1 Announce Type: new Abstract: Automatically generating slide decks from source documents is an important application of large language models (LLMs). Existing benchmarks primarily assess slide completeness and technical depth, while overlooking the target audience as a critical real-world factor. For instance, specialists demand rigorous proofs, whereas decision-makers prioritize actionable conclusions. To bridge this gap, we introduce X+Slides, a benchmark specifically designed for audience-conditioned slide generation. Built on a diverse corpus spanning 113 topics and seven
The rapid advancement of large language models (LLMs) is pushing the boundaries of automated content generation, making nuanced applications like audience-conditioned slide generation the next logical step in their development.
Improving automated content tailored to specific audiences significantly enhances efficiency and effectiveness in professional communication, impacting education, business, and expert domains.
The introduction of X+Slides provides a critical benchmark for evaluating LLM capabilities beyond basic content synthesis, focusing on audience adaptation and contextual relevance in communication.
- · AI developers
- · Consulting firms
- · Educators
- · Content creators
- · Manual presentation designers
- · Generic content generation tools
More sophisticated and context-aware AI-generated presentations become commonplace, reducing human effort in content adaptation.
The ability to finely tune communication for diverse stakeholders leads to improved decision-making processes and enhanced knowledge transfer across industries.
This refinement of AI communication tools could subtly reshape professional roles, empowering knowledge workers with advanced synthesis capabilities while shifting demand from basic content creation to strategic oversight.
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Read at arXiv cs.AI