Prompt Orchestration Markup Language
Large Language Models (LLMs) require sophisticated prompting, yet current
practices face challenges in structure, data integration, format sensitivity,
and tooling. Existing methods lack comprehensive solutions for organizing
complex prompts involving diverse data types (documents, tables, images) or
managing presentation variations systematically. To address these gaps, we
introduce POML (Prompt Orchestration Markup Language). POML employs
component-based markup for logical structure (roles, tasks, examples),
specialized tags for seamless data integration, and a CSS-like styling system
to decouple content from presentation, reducing formatting sensitivity. It
includes templating for dynamic prompts and a comprehensive developer toolkit
(IDE support, SDKs) to improve version control and collaboration. We validate
POML through two case studies demonstrating its impact on complex application
integration (PomLink) and accuracy performance (TableQA), as well as a user
study assessing its effectiveness in real-world development scenarios.
68a5366b6cf0bf898542ec8c
Yuge Zhang
68a5366b6cf0bf898542ec8d
Nan Chen
68a5366b6cf0bf898542ec8e
Jiahang Xu
claimed_verified
2025-08-20T08:51:16.884Z
62abdf657b037eafffc48808
https://cdn-avatars.huggingface.co/v1/production/uploads/1655430982462-noauth.jpeg
Jiahang Xu
user
Jiahang
68a5366b6cf0bf898542ec8f
Yuqing Yang
Prompt Orchestration Markup Language
Large Language Models (LLMs) require sophisticated prompting, yet current
practices face challenges in structure, data integration, format sensitivity,
and tooling. Existing methods lack comprehensive solutions for organizing
complex prompts involving diverse data types (documents, tables, images) or
managing presentation variations systematically. To address these gaps, we
introduce POML (Prompt Orchestration Markup Language). POML employs
component-based markup for logical structure (roles, tasks, examples),
specialized tags for seamless data integration, and a CSS-like styling system
to decouple content from presentation, reducing formatting sensitivity. It
includes templating for dynamic prompts and a comprehensive developer toolkit
(IDE support, SDKs) to improve version control and collaboration. We validate
POML through two case studies demonstrating its impact on complex application
integration (PomLink) and accuracy performance (TableQA), as well as a user
study assessing its effectiveness in real-world development scenarios.
POML addresses challenges in prompting Large Language Models by providing a structured, data-integrated, and format-sensitive markup language with templating and developer tools.
POML Prompt Orchestration Markup Language component-based markup specialized tags CSS-like styling system templating developer toolkit IDE support SDKs version control collaboration PomLink TableQA