Call for Papers

Areas of interest

IEEE SaTML expands upon the theoretical and practical understandings of vulnerabilities inherent to machine learning (ML), explores the robustness of learning algorithms and systems, and aids in developing a unified, coherent scientific community aiming to establish trustworthy machine learning. Topics of interest include (but are not limited to):

  • Novel attacks on machine learning
  • Novel defenses for machine learning
  • Secure and safe machine learning in practice
  • Verification of algorithms and systems
  • Machine learning system security
  • Privacy in machine learning
  • Forensic analysis of machine learning
  • Fairness and interpretability
  • Trustworthy data curation

Important dates

  • Paper submission deadline: Wednesday, September 24, 2025
  • Early reject notification: Wednesday, October 29, 2025
  • Interactive discussion & revision phase: November 19 - December 3, 2025
  • Decision notification: Wednesay, December 10, 2025
  • Conference dates: March 23-25, 2026

All deadlines are set to 11:59 PM AoE (Anywhere on Earth), which corresponds to UTC-12 time zone.

Submission categories

We solicit research papers, systematization of knowledge papers, and position papers:

  • Research Papers: These papers should present new work, evidence, or ideas related to secure and trustworthy machine learning. Submission must be up to 12 pages of body text, with unlimited additional space for references and appendices. Research papers must be well-argued and worthy of publication and​ ​citation,​ ​on​ ​one of the​ ​topics listed​ ​above.​

  • Systematization of Knowledge (SoK) Papers: These papers should either consolidate and clarify ideas in a major research area within secure and trustworthy machine learning or provide compelling evidence to support or challenge long-held beliefs in such areas. Submissions must be up to 12 pages of body text. SoK papers must include "SoK:" at the beginning of their title.

  • Position Papers: These papers should cover broader issues and visions related to secure and trustworthy machine learning, including open challenges, technical perspectives, educational aspects, societal impact, or notable research results. Submissions must be very well-argued and consist of 5 to 12 pages of body text. Position papers must include "Position:" at the beginning of their title.

Submission information

All submissions must be received by 11:59 PM AoE (UTC-12) on the day of the deadline. The submission site is available here:

Submitted papers must not substantially overlap with papers that have been published or accepted for publication, or that are simultaneously in submission to a journal, conference, or workshop with published proceedings. However, authors may choose to give talks about their work, post a preprint of the paper online, and disclose security vulnerabilities to vendors.

  • ⚠️ Double-blind review: SaTML follows a double-blind reviewing process. Submitted papers must be properly anonymized! They must (a) omit any reference to the authors' names or their institutions, and (b) cite the authors' own related work in the third person. It is important, however, to ensure that efforts to maintain anonymity do not compromise the quality of the submission or complicate the review process. Essential background references, for example, should not be omitted or anonymized. Please see this double-blind FAQ for the answers to many common concerns about double-blind reviewing.

  • ⚠️ Previous reviews: For papers that were previously rejected from another conference, authors must append prior reviews to their submission along with a description of how those reviews were addressed in the submission. The reviews must be anonymized, but otherwise unedited and complete. Authors are only required to include reviews from the last time the paper was submitted. Authors who try to circumvent this rule (e.g., by changing the title of the paper without significantly changing the contents) may have their papers rejected without further consideration, at the discretion of the PC chairs.

Submission format: Submissions must be a PDF file in two-column IEEE proceedings style. That is, authors must use \documentclass[conference]{IEEEtran} when preparing their paper. The number of allowed pages for a submission depends on the submission category, see above.

Authors need to closely follow these rules and precisely adhere to the format guidelines. Failure to comply with these rules is grounds for rejection.

Usage of LLMs

Authors are permitted to use LLMs when preparing their paper. However, while the conference does not ban authors from using LLMs or researching their security and privacy properties, authors must (a) carefully consider their decision to use LLMs and (b) are required to disclose and motivate the use of LLMs in their submission. If the authors choose to use LLMs in their work, they must use a separate and well-marked section titled “LLM usage considerations” at the end of their paper to make the relevant disclosures. This section will not count towards the page limit.

We ask that authors adhere to three key criteria with regards to their use of LLMs in the scientific process:

  • ⚠️ Originality: First, authors are responsible for the entire content of their paper, including all text and figures. While any tool may be used for writing, it is crucial that all content is accurate and original, ensuring transparency and maintaining the integrity of the research process. In particular, authors are responsible for the thoroughness of their literature review and must determine relevant prior work and cite it to ensure proper credit. If the authors have used LLMs to improve their writing, they should state: ‘LLMs were used for editorial purposes in this manuscript, and all outputs were inspected by the authors to ensure accuracy and originality.’

  • ⚠️ Transparency: Second, authors should carefully reason about the implications of using LLMs in their work. If LLMs are integral to the paper’s methodology, their use should be explicitly detailed. Any idea generated by an LLM should be independently developed and validated by the authors. Furthermore, authors must elaborate on how they handled limitations introduced in their work by their use of LLMs. Such limitations could for instance include difficulties to obtain results that are reproducible when the LLM used is not open sourced.

  • ⚠️ Responsibility: Third, authors should take care to develop LLMs (and ML models in general) responsibly. Any data collection towards training models should take into account relevant ethical considerations such as consent and data holder rights, including intellectual property. Authors also have to justify the need for the environmental footprint of their experiments to achieve their goals and support their methodology. We recognize calculating such a footprint is a technical challenge in itself. We refer the authors to the work of Lacoste et al. but welcome to hear any other good references (pcchairs@satml.org). We emphasize that the goal here is not to calculate the exact footprint but rather explain experimental choices made as part of the scientific process (e.g., why was an LLM necessary, why was a particular model size selected, how the authors minimized the volume of queries made, which hardware was used to run experiments).

Failure to comply with these rules is grounds for desk rejection without further review of the submission. We note that generative AI technology is rapidly evolving. Authors are encouraged to reach out proactively to the PC chairs should they face uncertainties about the above rules or how they apply to their research.

Reviewing process

All submissions to the conference will be evaluated based on their merits, particularly their relevance to the conference’s areas of interest, novelty, quality of execution, and presentation.

To decrease the load of reviewing on PC members, SaTML implements a two-round reviewing process. Each paper is initially assigned two reviews. If the PC chairs conclude that there is no path for acceptance at SaTML upon considering these initial reviews, the paper is early-rejected. This means that the paper is not assigned additional reviews and the authors are notified that their paper will not be included in the conference.

Author discussion phase

SaTML will have a discussion period during which authors can exchange messages with reviewers, respond to their questions, and address their comments through direct changes to the paper. To facilitate this, we will use an anonymous communication feature to enable interaction between authors and reviewers. Authors should primarily focus on correcting factual errors in the reviews and answering specific questions posed by the reviewers. New research results may also be discussed if they help clarify open questions. More instructions will be sent to the authors at the beginning of the discussion phase.

Submission decisions

For each submission, one of the following decisions will be made:

  • Accept: Papers in this category will be accepted for publication in the proceedings and presentation at the conference, possibly after making minor changes with the oversight of a shepherd (Minor Revision). Within one month of acceptance, all accepted papers must submit a camera-ready copy incorporating reviewer feedback. The papers will be published in the IEEE Computer Society Digital Library and authors are encouraged to also make them freely available via arXiv.

  • Major Revision: A limited number of papers will be invited to submit a major revision; such papers will receive a detailed summary of expectations for revision, in addition to standard reviewer comments. Authors will have a limited time window to submit a revision after the notification is sent. The authors should clearly explain in a well-marked appendix how the revisions address the comments of the reviewers. The revised paper will then be re-evaluated, and either accepted or rejected. We will assign the same set of reviewers. Authors can choose to withdraw their paper and not submit a revision.

  • Reject: Papers in this category are declined for inclusion in the conference.

Best paper award

Outstanding paper(s) will be selected by the Program Committee, with input from the Steering Committee, for the best paper award. The award will be announced at the conference. Best paper awards are intended to highlight papers which significantly challenge the state of the art in research areas relevant to SaTML.

Attendance for accepted papers

At least one author of accepted papers must present their work at the conference on site, and their papers will appear in the conference’s formal IEEE proceedings. In the event of difficulty obtaining visas for travel or other exceptional circumstances, exceptions may be made and will be discussed on a case-by-case basis.

If you have any questions, please email us at pcchairs@satml.org