Every year, CIKM highlights technologies and insights that materialize the big data and artificial intelligence vision of the future. The demo track at CIKM 2023 gives researchers and practitioners from academia, industry, and government an opportunity to showcase their prototypes and research ideas to the community. Accepted demo and resource papers will be part of the main conference proceedings.
Demos papers must be no more than 4 pages long, plus unlimited references (note that additional appendices are not allowed). Citing supplementary materials that are accessible online via platforms like osf.io or GitHub is permissible. However, reviewers have the discretion to decide whether or not they will review such materials. We cannot guarantee that these materials will be taken into consideration during the review process. The review of the demo and resource papers will be single-blind, which means that the authors should include their names and affiliations in the paper. All submissions will be reviewed by the Program Committee of the demos and resources track, who will evaluate the novelty of the technical features and/or research being presented, the research and/or development challenges, its expected impact, and its timeliness and relevance for the CIKM audience of practitioners and researchers.
Manuscripts should be submitted to CIKM 2023’s Easychair site in PDF format using the ACM's two-column template "sigconf", see https://www.acm.org/publications/proceedings-template. At least one author of each accepted paper must register to present the work as scheduled in the conference program.
All papers should be submitted via Easychair: https://easychair.org/conferences/?conf=cikm23
Guidelines and review rubric
Demo papers should describe the intended audience, point out the innovative aspects of the system being presented, and explain how those aspects contribute to the state of the art in knowledge, data, and information management. The submissions must also make clear what the audience will experience during the demo, what kind of functionality is supported, user scenarios, interface and interaction options provided, and how it is compared with existing systems (if any). Submissions that are case studies should also explain the case being demonstrated. Authors may also include a URL of a screencast video (up to 10 minutes), screenshots, and additional external material (e.g., shared code on GitHub).
Demo papers that describe case studies from mature systems will also be evaluated on the relevance of the system and innovative features and functionalities that are being included in the demonstration.
We follow the guidelines from the Program Chairs about the fair use of Large Language Models (LLMs), which can be found in the main call for papers. Papers that include text generated from a large-scale language model (LLM), such as ChatGPT, are prohibited unless the produced text is presented as a part of the paper’s experimental analysis. In essence, the policy expects the following:
The Large Language Model (LLM) policy for CIKM 2023 prohibits text produced entirely by LLMs (i.e., “generated”). This does not prohibit authors from using LLMs for editing or polishing the author-written text.
The LLM policy is largely predicated on the principle of being conservative with respect to guarding against potential issues of using LLMs, including plagiarism.
The LLM policy applies to CIKM 2023. We expect this policy to evolve in future conferences as we better understand LLMs and their impacts on scientific publishing.
Disclosure of funding and competing interests: Authors are required to provide an explicit disclosure of funding (financial activities supporting the submitted work) and competing interests (related financial activities outside the submitted work) that could result in conflicts of interest in a section (e.g., “Acknowledgments”) that should be added to the camera-ready version of accepted papers, but not in the version submitted for review (in order to maintain author anonymity). Furthermore, authors are required to read the AAAI code of conduct and ethics guidelines; submitting to CIKM implies that the authors agree to abide by these rules.
It is not allowed to submit papers that are identical (or substantially similar) to versions that have been previously published or accepted for publication or that have been submitted in parallel to other conferences (or any venue with published proceedings). Such submissions violate our dual-submission policy. There are several exceptions to this rule:
Submissions are permitted for papers presented or to be presented at conferences or workshops without proceedings or with only abstracts published.
Submission is permitted for papers that have previously been made available as a technical report or similar, e.g., on arXiv. In this case, the authors should not cite the report so as to preserve anonymity.
ACM Policy Against Discrimination
All authors and participants must adhere to the ACM's discrimination policy. For full details, please visit this site: https://www.acm.org/special-interest-groups/volunteer-resources/officers-manual/policy-against-discrimination-and-harassment
As a published ACM author, you and your co-authors are subject to all ACM Publications Policies https://www.acm.org/publications/policies, including ACM's new Publications Policy on Research Involving Human Participants and Subjects https://www.acm.org/publications/policies/research-involving-human-participants-and-subjects
- Demo and Resource track Email: cikm2023-demo@easychair.org
- Kokil Jaidka, National University of Singapore
- Hamed Alhoori, Northern Illinois University