IBM Research's Palette Trains a Small Model to Build Presentation Decks in Custom Design Languages

IBM Research has published details on Palette, a system that fine-tunes a small language model to generate presentation decks that conform to an organization's specific design language, brand guidelines, and slide structure conventions. Rather than relying on a large general-purpose model that produces generic output, Palette demonstrates that a compact, specialized model can learn the structural and stylistic rules of a custom deck format from relatively few examples. For developers building enterprise content generation tools, this is a practical case study in how fine-tuning small models on domain-specific style data can outperform prompting large models for format-constrained generation tasks. The approach is cost-efficient and keeps sensitive design assets within a controlled fine-tuning pipeline rather than exposing them to external APIs. The full methodology and model details are available on Hugging Face.