Instructions for Authors – Camera-Ready Paper

The camera-ready version of your paper is due by October 16, 2023 (23:59 Pacific Time).

Here are the instructions for preparing and submitting your camera-ready paper:

  1. The camera-ready paper should follow the template: 8-page main text + acknowledgment + references + appendix (optional). The appendix should be included at the end of the camera-ready PDF, rather than as a separate file. The template is available here. Please make sure to use “\usepackage[final]{corl_2023}”.

  2. If you have videos, code, datasets, and other supplementary materials that come with the paper, please host them on your own (e.g., YouTube, Github). There will be optional text fields on OpenReview for you to submit URLs for people to access your materials.

  3. A signed permission form for publication in PMLR (form available here). Please rename the pdf to <paperid_firstname_lastname>.pdf.

Please submit the camera-ready paper and the signed permission form through the OpenReview website by October 16, 2023 (23:59 Pacific Time). Please contact Yuke Zhu (yukez@cs.utexas.edu) if you have any questions.

Instructions for Authors-Initial submission

Submission Deadline: 8 June 2023

Submission Site:

https://openreview.net/group?id=robot-learning.org/CoRL/2023/Conference

Paper Submission Requirements and Instructions

Papers are submitted through OpenReview, via the link at the top of this page. All submissions should comply with the format and length indicated below.  CoRL is double-blind, which means that all papers and supplementary materials must be anonymized. The submitted papers and reviews will be publicly accessible after the decisions are made (August 30, 2023), but only accepted papers will be de-anonymized. Submitted papers will be reviewed by at least two reviewers. Accepted papers will appear in the Proceedings of Machine Learning Research.

Key Dates 

All deadlines are 11:59PM Pacific Time (UTC-7)

  • Paper submission open: May 15, 2023

  • Paper and supplemental materials submission deadline: June 8, 2023

  • Desk rejection: June 19, 2023

  • Reviews available: August 3, 2023                   

  • Discussion period: August 3-15, 2023

  • Paper acceptance notifications: August 30, 2023

  • Camera ready papers due: October 16, 2023

Submission Requirements and Instructions

Submissions are due June 8, 2023, 11:59PM Pacific Time, for both the paper and supplemental materials. 

The page limit is 8 pages plus n pages for references (8+n pages). Authors will have the option to submit a supplementary file containing further details, which the reviewers may decide to consult, as well as a supplementary video. All supplementary materials will be submitted through OpenReview as a single zip file.

All accepted papers will be presented in poster sessions, while selected papers will be invited for an oral spotlight presentation.

Review Criteria

Submissions will be evaluated based on the significance and novelty of the results, either theoretical or empirical. Results will be judged on the degree to which they have been objectively established and/or their potential for scientific and technological impact, as well as their relevance to robotic learning. Submissions should focus on a core robotics problem and demonstrate the relevance of proposed models, algorithms, datasets, and benchmarks to robotics. Authors are encouraged to report real-robot experiments or provide convincing evidence that simulation experiments are transferable to real robots. Papers with both experimental and theoretical results relevant to robot learning are welcome. However, submissions without a robotics focus may be considered for desk rejection. Our intent is to make CoRL a selective top-tier conference on robotic learning.

All submissions must include a Limitation Section, explicitly describing limiting assumptions, failure modes, and other limitations of the results and experiments, and how these might be addressed in the future. Please include the Limitation Section in the main paper within the 8-page limit.

Authors will have an opportunity to submit a response to reviewers and update the papers during the discussion period. Reviews and discussion of accepted papers will be made publicly available.

Desk Reject Criteria 

Process: ACs will identify the desk rejection candidates, using one of the criteria below as a justification. PCs will examine the candidates and make the final decision. We will err on the side of caution, and only desk reject papers when there is a consensus between all PCs and the AC.

The paper can be desk rejected for one of the four reasons: formatting issues, anonymity violation, missing Limitation Section, or scope.

  1. Formatting issues: The paper is either too long, or in an incorrect format.

  2. Anonymity violation: The main manuscript, supplemental materials, or a link provided in a paper identifies one or more of the authors.

  3. Missing or insufficient Limitation Section: All papers are required to have an honest and sufficiently encompassing Limitation Section. 

  4. Scope: All papers must have their core focus on contributing to the state-of-the-art in robot learning. Papers with no relation to learning (e.g. search algorithm for model-based planning) or no focus on a core robotics problem (e.g. a generic RL algorithm verified only in a simulator that may not be transferable to real robots, or improved performance on a standard Computer Vision benchmark) may be considered for desk rejection.

Submission Policy

We will not accept papers that are identical or substantially similar to papers that have previously been published or accepted for publication in an archival venue, nor papers submitted in parallel to other conferences or archival venues. Archival venues include conferences and journals with formally published proceedings, but do not include non-archival workshops. Submission is permitted for papers that have previously appeared only as a technical report, e.g. in arXiv.

Manuscript Template

Accepted papers will be published in PMLR. The manuscript template is available here.

Software Submission Instructions

Authors are encouraged to submit code alongside the paper. Authors should provide a readme file explaining how to run the author’s software, and, when applicable, how to use it to replicate experimental results given in the article. For code that include files not directly relevant to the scientific contribution of the paper, authors should indicate in the readme file which part of the code pertains to the scientific claims of the paper to ease the review process. Please verify that the submitted code abides to the same anonymity standard as the paper.

By default and unless authors specify a different license scheme, the code submitted along the paper will be protected under exclusive copyright linked to the paper ID. Reviewers will be strictly forbidden to use the code outside the review process.

Use of Code / Citation / Licensing

Be aware that you must always cite your sources, including in code you may be using for your research. Failing to do so may lead others to believe that you are the authors of the code, which would be considered as plagiarism. Authors are requested to explicitly cite sources in the code header and in the readme file.

Authors must also ensure that they have a license to modify or use other people’s code. See https://choosealicense.com/no-permission/ for information on how to act when you find code on the web that does not have a specific license.