<h2>Submission Instructions</h2>

<p>
    CoNEXT welcomes the submission of both long and short papers. All the submissions should be double-anonymous (more instructions below) and will be peer-reviewed. Per the anonymity guidelines, you must remove any author names.
</p>

<p>
    Long papers are the more traditional form to present technical work, and can have <b>max 16 pages</b> for main content, with unlimited pages for references and up to four pages for appendices.
</p>    
<p>
    Short papers are the preferred vehicle for contributions whose novelty and impact show the same technical excellence, and whose description does not need 16 pages. Short papers should be no more than <b>10 pages</b>, with unlimited pages for references and up to two pages for appendices. 
</p>
<p>    
    Upon acceptance, both short and long papers will be scheduled for publication in the closest issue of the <a href="https://dl.acm.org/journal/pacmnet" target="_blank">Proceedings of the ACM on Networking (PACMNET)</a>.
</p>

<h3>Submission portal</h3>

<p>
    Submit your contributions to <a href="https://conext26-june.hotcrp.com " target="_blank" rel="noopener">https://conext26-june.hotcrp.com</a>.
</p>

<h2>Submission Template</span></h2>

<p>
    <b><u>Both long and short submissions use the same template!</u></b>
</p>
<p>
    Both types of submission needs to be <b>double-anonymous</b>.
</p>

<h3>Long papers / PACMNET papers</h3>

<p><b><u>Long papers</u></b> are the more traditional form to present technical work.</p>

<p>
    Long papers need to adopt the <b>single-column, 10pt, ACM <tt>acmsmall</tt> template</b>.
</p> 
<p>
    ACM has partnered with Overleaf, a free cloud-based, collaborative authoring tool, to provide an ACM LaTeX authoring template. You can find it at this <a href="https://www.overleaf.com/latex/templates/association-for-computing-machinery-acm-small-standard-format-template/sksvmbxyfhnw">link</a>.
</p>

<p>
    When opening the template in overleaf, please checkout the <tt>sample-acmsmall.tex</tt> and set up the latext class
    as
    <tt>\documentclass[acmsmall,anonymous,review]{acmart}</tt> (by default the template is already with 10pt font size).
</p>

<p>
    Complementary to the new template, the following rules apply
<ul>
    <li>Submission can have <b>max 16 pages for main content, max 4 pages for appendices, and unlimited pages for references</b></li>
    <li>Final CR preparation handled directly by Sheridan - that will provide also detailed instructions</li>
    <li>Accepted papers will appear to the designated PACMNET issue</li>
</ul>
<p>

<h3>Short papers / PACMNET Papers</h3>

<p>
    <b><u>Short papers</u></b> are the preferred vehicle for contributions whose novelty and impact show the same technical excellence, and whose description does not need 16 pages.
</p>
<p>
    Short papers need to adopt the <b>single-column, 10pt, ACM <tt>acmsmall</tt> template</b>.
</p>
<p>
    Short papers will be reviewed with a more open mind towards the scope of evaluation or breadth of topics compared to long papers. Note that position papers, critiques of networking research, and ideas that are not yet fully complete or evaluated are a better fit for the HotNets workshop. We welcome experience submissions that clearly articulate lessons learned, as well as submissions that refute prior published results.
</p>
<p>
    ACM has partnered with Overleaf, a free cloud-based, collaborative authoring tool, to provide an ACM LaTeX authoring template. You can find it at this <a href="https://www.overleaf.com/latex/templates/association-for-computing-machinery-acm-small-standard-format-template/sksvmbxyfhnw">link</a>.
</p>

<p>
    When opening the template in overleaf, please checkout the <tt>sample-acmsmall.tex</tt> and set up the latext class
    as
    <tt>\documentclass[acmsmall,anonymous,review]{acmart}</tt> (by default the template is already with 10pt font size).
</p>

<p>
    Complementary to the new template, the following rules apply
<ul>
    <li>Submission can have <b>max 10 pages for main content, max 2 pages for appendices, and unlimited pages for references</b></li>
    <li>Final CR preparation handled directly by Sheridan - that will provide also detailed instructions</li>
    <li>Accepted papers will appear to the designated PACMNET issue</li>
</ul>
</p>

<h3>Double-anonymous requirements</h3>
<p>
    All submitted papers will be assessed through a double-anonymous review process. This means that the authors do not see who are the reviewers and the reviewers do not see who are the authors. As an author, you should do your best to ensure that your paper submission does not directly or indirectly reveal the authors' identities. The following steps are minimal requirements for a double-anonymous submission:
</p>
<ul>
    <li>Remove all personal information about the authors from the paper (e.g., names, affiliations)</li>
    <li>Remove acknowledgements to organizations and/or people</li>
    <li>When referring in the paper to your previous work, this should be done similarly to any other work, as if you are not an author of that work.</li>
    <li>Do not add references to external repositories or technical reports that can be used to identify any of the authors or institutions/organizations. You are encouraged to mention that your code will be made available during your submission.</li>
    <li>Uploading a version of the paper to a non-peer-reviewed location is acceptable. The authors should however avoid advertising the paper on popular mailing lists and social media.</li>
</ul>

<p>
At the same time, PC members should not actively try to de-anonymize the authors' identities. Any violation of the double-anonymous reviewing process should be reported to the PC chairs.
</p>

<h3>Ethical concerns</h3>
<p><b>All papers must include a statement or subsection about ethical issues raised by the work.</b> In limited cases, this could simply be a sentence disclaiming ethical issues, but work involving human subjects or potentially sensitive data (e.g., user traffic, social network information, censorship evasion) must clearly discuss the relevant issues. Papers that do not include an ethics statement may be rejected.</p>

<p>Papers must follow basic precepts of ethical research and subscribe to community norms. Works must also show respect for norms around privacy, secure storage of sensitive data, voluntary and informed consent for human subjects and users who might be placed at risk, avoiding deceptive practices when not essential, beneficence (maximizing the benefits to an individual or to society while minimizing potential harm to an individual), and risk mitigation. Authors may want to consult the Menlo Report and the ACM ethics policy for further information on ethical principles, and they may find the Allman/Paxson paper in IMC 2007 helpful for a perspective on ethical data sharing.</p>

<p>By submitting your article to an ACM Publication, you are hereby acknowledging that you and your co-authors are subject to all <a href="https://www.acm.org/publications/policies" target="_blank">ACM Publications Policies</a>, including ACM's new <a href="https://www.acm.org/publications/policies/research-involving-human-participants-and-subjects" target="_blank">Publications Policy on Research Involving Human Participants and Subjects</a>. Alleged violations of this policy or any ACM Publications Policy will be investigated by ACM and may result in a full retraction of your paper, in addition to other potential penalties, as per ACM Publications Policy.</p>

<p>Many organizations have an ethics review process, sometimes called an Institutional Review Board (IRB), and in many projects, IRB involvement is appropriate. IRB approval of research is an important factor and should be mentioned, but the program committee will independently evaluate the ethical soundness of the work just as they evaluate its technical soundness.</p>

<p>The Program Committee takes a broad view of what constitutes an ethical concern, and the PC chairs may reach out to authors during the review process if questions arise.</p>

<h3>Use of Generative AI</h3>

<p>While generative AI systems—such as large language models (LLMs)—are powerful and useful tools, there remain open questions as to how and which data they use to train, raising potential concerns over integrity and confidentiality. The ACM has established a set of guidelines pertaining to how authors and reviewers can use generative AI. We summarize some of the main points below, but we refer authors to the following links. Failure to adhere to these guidelines can result in paper rejection.</p>

<p>By authors: The <a href="https://www.acm.org/publications/policies/frequently-asked-questions" target="_blank">ACM's author guidelines</a> state that authors are allowed to use generative AI in limited ways, and that their use must be acknowledged in the paper. For small portions of text (phrases or sentences), papers must include a footnote stating that it was generated by AI; for larger portions of text, graphics, and other content, authors must disclose in the Appendix what content was generated by an AI, along with the specific tools and versions used. Please refer to the ACM guidelines for more specific instructions.</p>

<p>By reviewers: Reviewers are not allowed to upload any portion of the submitted papers to generative AI tools. However, according to the <a href="https://www.acm.org/publications/policies/peer-review" target="_blank">ACM's peer review guidelines</a>, reviewers may upload the content of their own reviews to generative AI "with the sole purpose of improving the quality and readability of reviewer reports for the author, provided any and all parts of the review that would potentially identify the submission, author identities, reviewer identity, or other confidential content is removed prior to uploading into third party tools."</p>