NeurIPS 2025 Call for Position Papers
We invite the submission of position papers to be published at the NeurIPS 2025 conference. Position papers make an argument for a viewpoint or perspective about what should be done, in contrast to research track papers, which report on advances that have already been accomplished. Position papers also generally adopt a meta-level perspective on the field of machine learning, with wider scope than any individual area.
The review criteria for position papers differs from those of the main conference track. Submissions to the main NeurIPS conference track emphasize original research and novel results. In contrast, submissions to the position paper track will be judged primarily on whether they present a compelling position that warrants greater exposure within the machine learning community (regardless of whether a reviewer agrees with the position). The goal of this track is to highlight papers that stimulate (productive, civil) discussion on timely topics that need our community’s input. Controversial topics are welcome.
Position papers should meet standard NeurIPS expectations for scholarship, including the use of evidence and reasoning to support claims, inclusion of relevant background and context, and the attribution of work via appropriate citations. Accepted position papers will be presented at the conference and included in the conference proceedings.
We want to hear your ideas. What is the field getting right? Getting wrong? How can our work be used for positive or destructive ends in government, military, medicine, public policy, or law? What are open problems that we should focus more on? Or less? Position papers may address any aspect relevant to machine learning, including (but very much not limited to) discussions such as the following:
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Concerns about data legality, copyright, and intellectual property in model training procedures
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The role of privacy in machine learning training and deployment
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The role of open-source versus closed-source ML models for research
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Regulation of ML technology (licensing, evaluation, disclosures, post-deployment monitoring, etc.)
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Ethical considerations when conducting ML research or deploying ML systems
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The role of symbolic AI within the context of modern deep learning
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User guidance for responsible use of ML tools, services, applications, etc.
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What the next generation of ML researchers needs to know
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How we can improve the ways that we conduct and evaluate machine learning research
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How we can improve the beneficial impact of our community’s work
We encourage you to browse the position papers that were published at ICML 2024 for examples (and ideas to build on, or from which to offer an alternative position).
Policies and Requirements
The formatting requirements (including 8-page limit), double-blind reviewing, policies (including plagiarism, dual submission, use of generative AI, ethics review, etc.), and deadlines for position papers are shifted slightly later compared to those of the main conference (see the main Call for Papers). Please note the requirement for a “lay summary” of papers (including position papers) that are accepted for publication.
The following additional requirements apply to position papers:
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Title: The title should state the position.
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Examples of appropriate titles:
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Quantum Atelic Learning Methods Should Employ Psychic Insights"
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Stop Research on Psychic Properties of Machine Learning"
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Non-example titles that do not state a position clearly:
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Psychic Quantum Atelic Learning"
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A Perspective on Psychic Quantum Atelic Learning"
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Abstract: The abstract must briefly state the position (e.g., “This position paper argues that <statement of the position>.”).
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Introduction: The introduction must state the position, using bold text.
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Alternative Views: The paper can (if appropriate) include an “Alternative Views” section in the main body of the paper (not in an appendix) that describes and addresses one or more viable (not strawmen) positions that are opposed to the paper’s position.
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Papers that describe new research without advocating a position are not responsive to this call and should instead be submitted to the main paper track.
Important Dates and Submission Site
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Submission site open: April 5, 2025
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Suggested OpenReview account creation deadline: May 8, 2025 AoE. (If you do not already have an OpenReview account, please register by this date; otherwise we cannot guarantee that your account will be activated in time.**)
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Full paper submission deadline: May 22, 2025 AoE
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Discussion and meta-review period: July 24–August 28, 2025 AoE
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Author notification: Sept 18, 2025
Position papers can be submitted through OpenReview: openreview.net/group?id=NeurIPS.cc/2025/Position_Paper_Track
Note: Regular research papers should be submitted through a separate OpenReview site, as outlined in the Call for Papers.
OpenReview: All authors must have an OpenReview account. It is strongly recommended that you sign up for OpenReview (or associate your existing account) with an institutional email. If you sign up for OpenReview with an institutional email, your account will be activated immediately; otherwise, it can take up to 2 weeks for your account to be activated.
Reviewing
Position papers will be reviewed according to the following criteria, which differ from those employed by the main track:
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Position: The paper clearly states a position on a machine learning topic (policy, implementation, deployment, monitoring, etc.). Examples include (but are not limited to) an argument in favor of or against a particular research direction (not a particular algorithm or solution), a call to action, a value statement, a policy proposal, or a recommendation for changes to how we conduct and evaluate research.
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Papers that describe new research without advocating a position are not responsive to this call and should instead be submitted to the main paper track.
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Support: The paper supports its position with clear reasoning and evidence where appropriate.
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Significance: The paper demonstrates that the topic is important, in terms of scope, impact, timeliness, risks, benefits, etc.
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Discussion potential: The topic is likely to inspire constructive, useful discussion within the NeurIPS community. The reviewer need not agree with the stated position.
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Alternative views: The paper describes and addresses one or more viable (not strawmen) positions that are opposed to the paper’s position (if relevant).
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Communication quality: The paper is well organized and clearly written.
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Context: The paper includes a discussion of (and citations to) literature and events relevant to the stated position.
Questions?
Please select “Position Paper Chairs” on the help form and submit your questions here:
/Help/Contact?select=Position