CI 2026  /  Submit  /  General Submission Instructions

General Submission Instructions

Submission Templates

All submissions should use one of the following templates and must be converted to PDF at the time of submission:

All authors should submit manuscripts for review in a single column format. For the Word Template, follow the embedded instructions to apply the paragraph styles to your various text elements.

LaTeX Setup Instructions: To use the LaTeX Template within Overleaf, select New Project → Upload Project and upload the compressed .zip file downloaded from the link above. Please use the "sigconf" proceedings layout template to construct your manuscript (see sample-sigconf.tex located within the samples directory). On the first active line of the Code or Visual Text Editor, replace \documentclass[sigconf]{acmart} with \documentclass[manuscript]{acmart} to cleanly render a single-column format review copy. Please review the documentation files and ACM’s LaTeX best practices guide should any formatting questions arise.

Policy on Using Large Language Models (LLMs)

In line with other SIGCHI conferences (e.g., CHI), and computing conferences (e.g., CVPR and KDD), CI and HCOMP 2026 employ the following policy on the use of Large Language Models in authoring submissions.

Text generated from a large-scale language model (LLM), such as ChatGPT, must be clearly marked where such tools are used for purposes beyond editing the author’s own text. Please carefully review the ACM Policy on Authorship before you use these tools. This SIGCHI blog post describes approaches to acknowledging the use of such tools and we refer to it for guidance.

Note that the LaTeX template will default to hiding the Acknowledgements section while in review mode; please make sure that any LLM disclosure is available in your submitted version. We will investigate submissions brought to our attention and desk reject submissions where LLM use is not clearly marked or where an LLM is not appropriately used (e.g., including fake references generated by LLM, relying on AI tools to generate ideas in the manuscript, etc.).