
Sebastian Baltes developed and maintained the se-ubt/llm-guidelines-website, a Jekyll-based platform for publishing empirical guidelines on Large Language Models. Over five months, he delivered features such as automated content generation, submodule integration for research papers, and enhanced bibliographic metadata, improving both usability and data quality. His work included refining documentation, standardizing terminology, and implementing deployment workflows using GitHub Actions and YAML configuration. By leveraging technologies like JavaScript, LaTeX, and shell scripting, Sebastian ensured reliable builds, streamlined content management, and facilitated collaboration. The resulting platform supports rigorous research dissemination and enables teams to efficiently share, update, and reference methodological guidelines.
March 2026 — Focused on documentation clarity and cross-repo alignment for se-ubt/llm-guidelines-website. Delivered standardized terminology (Large Language Models), refined HTML conventions and study guidelines, and synchronized the LLM Guidelines Paper submodule to the latest changes. No major bugs fixed this month; the work improves onboarding, reduces ambiguity, and ensures consistent references to the latest research paper across the site.
March 2026 — Focused on documentation clarity and cross-repo alignment for se-ubt/llm-guidelines-website. Delivered standardized terminology (Large Language Models), refined HTML conventions and study guidelines, and synchronized the LLM Guidelines Paper submodule to the latest changes. No major bugs fixed this month; the work improves onboarding, reduces ambiguity, and ensures consistent references to the latest research paper across the site.
February 2026 monthly summary for se-ubt/llm-guidelines-website: Delivered core site enhancements, tighter integration with the paper repository, automated content generation, and stability fixes that boost reliability and maintainability. Business value includes faster site builds, improved resource sharing, and easier distribution of checklists and documentation.
February 2026 monthly summary for se-ubt/llm-guidelines-website: Delivered core site enhancements, tighter integration with the paper repository, automated content generation, and stability fixes that boost reliability and maintainability. Business value includes faster site builds, improved resource sharing, and easier distribution of checklists and documentation.
December 2025 monthly summary focused on delivering data-quality enhancements to bibliographic metadata for the se-ubt/llm-guidelines-website. Key feature delivered: added a Journal field to bibliographic entries in literature.bib, enabling richer metadata, improved searchability, and more accurate citations. No major bugs fixed in this period; changes are backward-compatible and well-documented with a traceable commit.
December 2025 monthly summary focused on delivering data-quality enhancements to bibliographic metadata for the se-ubt/llm-guidelines-website. Key feature delivered: added a Journal field to bibliographic entries in literature.bib, enabling richer metadata, improved searchability, and more accurate citations. No major bugs fixed in this period; changes are backward-compatible and well-documented with a traceable commit.
November 2025: Delivered governance and research-quality improvements for the se-ubt/llm-guidelines-website repository. Key work includes (1) Contributor Affiliation Metadata Update to reflect Heidelberg University for Sebastian Baltes, ensuring accurate attribution; (2) Guidelines Enhancements for AI Evaluation and LLM Tools, including a cited statistical evaluation method, minor edits, and added references, strengthening evaluation rigor and bias awareness in qualitative AI research. Together, these changes improve attribution accuracy, documentation quality, and readiness for audits, while raising methodological rigor in AI evaluation.
November 2025: Delivered governance and research-quality improvements for the se-ubt/llm-guidelines-website repository. Key work includes (1) Contributor Affiliation Metadata Update to reflect Heidelberg University for Sebastian Baltes, ensuring accurate attribution; (2) Guidelines Enhancements for AI Evaluation and LLM Tools, including a cited statistical evaluation method, minor edits, and added references, strengthening evaluation rigor and bias awareness in qualitative AI research. Together, these changes improve attribution accuracy, documentation quality, and readiness for audits, while raising methodological rigor in AI evaluation.
November 2024: Delivered foundational LLM Guidelines Website with scaffolded Jekyll site, enabling rapid publication of empirical guidelines for LLM studies. Established deployment workflow and dependency configuration, enabling reliable builds. Implemented roadmap section and UI navigation icon improvements, including branding asset (GitHub logo). No major bug fixes reported this month. Impact: provides a repeatable, publish-ready platform that accelerates knowledge sharing and standardizes guidelines for teams, reducing time to publish and improving discoverability. Technologies: Jekyll static site, Git versioning, deployment automation, asset management, UI/navigation enhancements.
November 2024: Delivered foundational LLM Guidelines Website with scaffolded Jekyll site, enabling rapid publication of empirical guidelines for LLM studies. Established deployment workflow and dependency configuration, enabling reliable builds. Implemented roadmap section and UI navigation icon improvements, including branding asset (GitHub logo). No major bug fixes reported this month. Impact: provides a repeatable, publish-ready platform that accelerates knowledge sharing and standardizes guidelines for teams, reducing time to publish and improving discoverability. Technologies: Jekyll static site, Git versioning, deployment automation, asset management, UI/navigation enhancements.

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