KTBox: A Modular LaTeX Framework for Semantic Color, Structured Highlighting, and Scholarly Communication

TL;DR

The paper tackles the problem of inconsistent and non-portable visual emphasis in scientific manuscripts by introducing ktbox, a modular LaTeX framework that unifies semantic color palettes, structured highlight boxes, taxonomy trees, and author metadata. It combines independent yet interoperable components—ktcolor for semantic palettes, ktbox for highlight environments, ktlrtree for left-to-right taxonomy trees, and ktorcid for ORCID metadata—to enable template-agnostic, reproducible formatting across articles, posters, and presentations. Key contributions include a tcolorbox-based structural layer with auto-numbered takeaways and wide-format options, a semantic color design with light/dark themes, and the ktlrtree taxonomy extension that integrates visual hierarchy with scholarly citations. The framework aims to improve clarity, portability, and authoring efficiency by treating styling as reusable building blocks rather than cosmetic adornments, with practical impact for diverse scholarly formats and workflows.

Abstract

The communication of technical insight in scientific manuscripts often relies on ad-hoc formatting choices, resulting in inconsistent visual emphasis and limited portability across document classes. This paper introduces ktbox, a modular LaTeX framework that unifies semantic color palettes, structured highlight boxes, taxonomy trees, and author metadata utilities into a coherent system for scholarly writing. The framework is distributed as a set of lightweight, namespaced components: ktcolor.sty for semantic palettes, ktbox.sty for structured highlight and takeaway environments, ktlrtree.sty for taxonomy trees with fusion and auxiliary annotations, and ktorcid.sty for ORCID-linked author metadata. Each component is independently usable yet interoperable, ensuring compatibility with major templates such as IEEEtran, acmart, iclr conference, and beamer. Key features include auto-numbered takeaway boxes, wide-format highlights, flexible taxonomy tree visualizations, and multi-column layouts supporting embedded tables, enumerations, and code blocks. By adopting a clear separation of concerns and enforcing a consistent naming convention under the kt namespace, the framework transforms visual styling from cosmetic add-ons into reproducible, extensible building blocks of scientific communication, improving clarity, portability, and authoring efficiency across articles, posters, and presentations.

Figures (5)

• Figure 1: Dependency workflow of the ktbox framework, annotated with semantic color design, structural environments, taxonomy trees, and ORCID integration. Outputs (Article, Poster, PPT) are grouped under a unified brace.
• Figure 2: Illustrative taxonomy tree (TT) for computer vision architectures. Each node highlights representative architectures with and without citations mix to show flexibility of TT.
• Figure 3: Conceptual taxonomy of the KTBox framework. Each module of the system is represented as a branch, with cross-references to the respective sections in the paper. Curly braces group related components, and the split boxes summarize their description and limitations or design principles and extensions. This representation mirrors the style of learning technique taxonomies but focuses on the internal architecture of the framework.
• Figure 4: Computer Vision architectures
• Figure 5: Conceptual taxonomy of the KTBox framework. Each module of the system is represented as a branch, with cross-references to the respective sections in the paper. Curly braces group related components, and the split boxes summarize their description and limitations or design principles and extensions. This representation mirrors the style of learning technique taxonomies but focuses on the internal architecture of the framework.