The extended abstract must be written in clear and concise English.

The submission must not exceed one A4 page, including the title, author information, abstract text, keywords, equations, figures, tables, acknowledgements, and references.

Authors must prepare the extended abstract using one of the official NUMSTAT 2026 templates available in LaTeX, MS Word, or OpenDocument format.

The prescribed page size, margins, font sizes, line spacing, and overall formatting must not be altered.

The title should be concise and clearly reflect the subject of the work.

Provide the full names and affiliations of all authors. Mark the corresponding author with a superscript asterisk (*) and provide the corresponding author’s email address.

 The name of the presenting author must be underlined. When the corresponding author is also the presenting author, both the underline and the asterisk should be used.

 The abstract should clearly present: 

Authors are encouraged to include specific or quantitative results rather than only describing the proposed work.

Provide three to five keywords relevant to the submission.

Figures and tables, when included, must be legible, appropriately numbered, and referred to in the text.

References should be concise, consistently formatted, and limited to those essential to the submitted work.

The extended abstract must contain original work relevant to the themes and tracks of NUMSTAT 2026.

Before submission, authors should ensure that the document contains no comments, tracked changes, annotations, or identifying file metadata that is not intended for review.

The final extended abstract must be submitted in PDF format through the online submission portal. Editable source files should be retained by the authors and may be requested later.

Submissions will be evaluated on the basis of relevance, originality, technical quality, clarity, and significance of the work.

Authors are responsible for the accuracy of all information provided in the submission, including author names, affiliations, and contact details.

All extended abstracts will be screened using Turnitin. After excluding the reference section, the overall similarity index must be less than 20%, and similarity from any single source must not exceed 1%.

Large Language Models and other generative AI tools cannot be listed as authors. Authors must disclose any use of generative AI or AI-assisted tools during the preparation of the extended abstract and remain fully responsible for the accuracy, originality, and integrity of the submitted content.