ICML 2024 Call For Position Papers
We invite submissions for a new position paper track at the ICML 2024 conference. The field of machine learning is broadening at a rapid pace, and many important contributions to the field do not fit the typical mold of a traditional conference research paper: instead, they have discussed an ongoing trend, or advocated for a particular viewpoint or perspective on the field. This track aims to encourage the publication and dissemination of ideas and conversation within the ICML conference itself.
The evaluation criteria for position papers differs from those of the main conference track. Submissions to the main ICML 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 perspective that warrants greater exposure within the machine learning community (irrespective of whether a reviewer agrees or not with the given position, though we will below clarify additional reviewing criteria). The goal of this track is to highlight papers that stimulate (productive, civil) discussion on timely topics that need our community’s input.
Position papers should meet standard ICML expectations for scholarship, including the use of evidence and reasoning to support claims, inclusion of relevant background and context, and the attribution of others’ work via appropriate citations. Accepted position papers will be presented at the conference and included in the conference proceedings. Position papers will be presented either as orals or posters, in the same proportion as accepted regular-track papers.
We want to hear your ideas. Position papers may address any aspect relevant to machine learning, including (but very much not limited to) discussions such as the following:
- The strengths and limitations of current LLM approaches to intelligent systems
- The role of open-source versus closed-source ML models for research
- Data legality and copyright aspects of model training procedures
- The role of privacy in machine learning training and deployment
- Implications of the shift to foundation models for many machine learning tasks
- Assessing ongoing trends in machine learning scholarship
- Concerns of the AI ethics community or the AI/AGI safety community
- The use of ML technology in social media or other venues that raise concerns about the spread of misinformation
- Research priorities for ML
- How can we improve the beneficial impact of our community’s work
The formatting (including page limit), policies, and deadlines for position papers are identical to those of the main conference, as described in the main call for papers. Specifically, papers are a maximum of 8 pages using the same ICML Style Template File, and with the same deadline (February 1, AoE) as the main track, and also will use double blind reviewing. See the main Call for Papers for additional information. Notably, position papers are subject to all the same requirements as traditional papers, including the plagiarism policy, dual review policy, and potential for ethics review. To clearly delineate submissions to this track, position papers must be titled beginning with the phrase “Position Paper: <Paper title>”
Position papers will be reviewed by ICML reviewers who explicitly opt in by checking the appropriate box within the OpenReview system. Position papers will be reviewed according to the following criteria, which differ from those employed by the main track.
1. Position: The paper clearly states a position on a machine learning topic (research, implementation, deployment, monitoring, etc.). Examples include (but are not limited to) an argument in favor or against a particular research priority, a call to action, a value statement, a statement of concern about ICML community procedures, or a recommendation for changes to how we conduct and evaluate research.
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.
2. Support: The paper supports its position with clear reasoning and evidence where appropriate.
3. Significance: The paper demonstrates that the topic is important, in terms of scope, impact, timeliness, risks, benefits, etc.
4. Discussion potential: The topic is likely to inspire constructive, useful discussion within the ICML community. The reviewer need not agree with the stated position.
5. Communication quality: The paper is well organized and clearly written.
6. Context: The paper includes a discussion of (and citations to) literature and events relevant to the stated position.