CPAL has two submission tracks:
The submission and review stage will be double-blind. We use OpenReview to host papers and record discussions between authors and reviewers. Before the end of the Authors-Reviewers Discussion Stage, authors can participate in the discussion as well as update their submission at any time. After that, there will be an internal discussion period amongst reviewers and ACs with the aim of summarizing the review process, after which the final decisions are made by ACs.
After the notification deadline, accepted and opted-in rejected papers will be made public and open for non-anonymous public commenting. Their anonymous reviews, meta-reviews, author responses and reviewer responses will also be made public. Authors of rejected papers will have two weeks after the notification deadline to opt in to make their de-anonymized rejected papers public in OpenReview.
Submissions that are substantially similar to papers previously published, or submitted in parallel to other peer-reviewed venues with proceedings or journals may not be submitted to the Proceedings Track. Papers previously presented at workshops are permitted, so long as they did not appear in a conference proceedings (e.g., CVPRW proceedings), a journal or a book.
The existence of non-anonymous preprints (on arXiv or other online repositories, personal websites, social media) will not result in rejection. Authors may submit anonymized work to CPAL that is already available as a preprint (e.g., on arXiv) without citing it.
Accepted papers will be published in the Proceedings for Machine Learning Research (PMLR). Full proceedings papers can have up to nine pages with unlimited pages for references and appendix. Upon acceptance of a paper, at least one of the authors must join the conference.
We follow the rule by NeurIPS 2023, quoted as follows:
“We welcome authors to use any tool that is suitable for preparing high-quality papers and research. However, we ask authors to keep in mind two important criteria. First, we expect papers to fully describe their methodology, and any tool that is important to that methodology, including the use of LLMs, should be described also. For example, authors should mention tools (including LLMs) that were used for data processing or filtering, visualization, facilitating or running experiments, and proving theorems. It may also be advisable to describe the use of LLMs in implementing the method (if this corresponds to an important, original, or non-standard component of the approach). Second, authors are responsible for the entire content of the paper, including all text and figures, so while authors are welcome to use any tool they wish for writing the paper, they must ensure that all text is correct and original.”
We meanwhile aim to showcase the latest research innovations at all stages of the research process, from work-in-progress to recently published papers. Concretely, we ask members of the community to submit to OpenReview either:
- A conference-style submission describing the work, which may be prepared using the CPAL style files, but need not conform to any specific formatting requirements (e.g., page limits);
- A poster (in PDF form) presenting results of work-in-progress;
- The camera-ready version of work that has been published prior (e.g., conferences, journals).
Please also upload a short (250 word) abstract to OpenReview. OpenReview submissions may also include any of the following supplemental materials that describe the work in further detail:
- A link to a blog post (e.g., distill.pub, Medium) describing results.
- Appendices with detailed derivations and additional experiments.
This track is non-archival and has no proceedings. We permit under-review or concurrent submissions, as well as papers officially accepted by a journal or conference within 12 months of the submission deadline for the Recent Spotlight Track. Reviewing will be performed in a single-blind fashion (authors should not anonymize their submissions), and will be held with the same high quality bar with the Proceedings Track.