Authorship and Anonymization

Policy on Use of Generative AI

HRI 2027 follows the ACM Policy on Authorship and the ACM Publications Policy FAQ. We do not impose requirements beyond ACM's.

• Using generative AI to help write your submission is permitted and does not need to be disclosed. Your submission as a whole must still be an accurate representation of your own work and novel intellectual contributions, and must not be primarily the product of a tool's generative capabilities.
• If you used generative AI in conducting the research, you must describe that use in detail in the methods section of your paper. This applies to research design and methodology, creation or selection of data sources, experiment design, data generation, collection, or analysis, coding, model implementation, simulations, testing, validation, and deployment. It also applies to artifacts that bear on your conclusions, such as code, datasets, and figures.
• Generative AI tools cannot be listed as authors. All named authors are responsible and accountable for every part of the submission, including any AI-generated material, regardless of its source. ACM may reject a submission before publication, or retract it afterwards, where content-integrity problems arising from AI use are identified.

Anonymizing Submissions

The HRI conference full papers, as well as other submission types such as Short Contributions, alt.HRI, or Late Breaking Reports, follow a double-blind review process, requiring authors to prepare an anonymized submission.

To prepare an anonymized submission, authors are expected to remove author and institutional identities from the cover page, the acknowledgments section, and the PDF meta-data. Institution information should also be removed from the body of the text. For instance, use “…participants were recruited from a university campus” instead of “…participants were recruited from <university name>.”

Additionally, we recommend removing marks that identify institutional affiliation from images and supplementary videos (e.g., institutional attire, logos) as much as possible. However, pictures of robots used and study setup, in general, do not need to be anonymized, even if the robot uniquely identifies your group.

We ask that authors leave citations to their prior work un-anonymized in order to provide a more comprehensive review of prior work including the authors’ own research. Authors citing their own prior work should discuss it in the third person. For instance, instead of “Our prior work [6]…” use “Prior work by [6]…”

The checklist below summarizes the anonymization procedure.

Posting Articles Publicly Online (e.g., own website, arXiv)

To maintain the double-blind review process, we request authors refrain from posting their articles online until the final notification date.