We invite participants to submit in PDF format a 2-page extended abstract (non-archival) in the area of Deep Learning. References can go beyond the page limit.
Authors can download the latest packaged template here or follow the instructions in the repository to clone the template. Detailed style guidelines can be found within the main.tex or in the compiled versions.
The reviewing process for NLDL Abstract Track is single-blind, meaning that reviewers will know the authors' identities but the reviewers identities are hidden.
Submissions will not be public. Reviewers are not allowed to share the papers they receive for review or use the material for any purpose other than providing their review. After the reviews, there will be a decision made by the Area Chairs handling the submissions. There is no rebuttal or discussions about the reviews, and the decisions are final.
While we encourage the discussion of novel and ongoing work, we allow authors to present their published work related to the topics of the conference in this track. Authors must disclosed that the submission is for the presentation of an already published work in the submission form.
The authors are expected to summarize their work into a 2-page extended abstract for the reviewers to evaluate the appropriateness of the topics to the conference.
The authors on the submitted abstract must be a subset of the original published work authors. That means that you cannot add new authors that were not in the original submission. You can have less authors, though.
Q. Can we please have an extension on the paper registration or submission deadline?
A. NO. Furthermore, any incomplete submission or a submission not meeting required criteria will be deleted.
Q. Can I update my paper’s information (e.g., title, abstract, author list) after the paper registration deadline?
A. You can update the title and abstract until the submission deadline. You can also reorder the author list until the submission deadline. However, after the deadline, you can no longer create new submissions or add/delete authors of your submission(s).
Q. Can I add/remove authors after my paper has been accepted?
A. NO. After the registration deadline, the author list is considered final. Changes to the authorship order may be done freely between the registration and submission deadlines. Further changes to the authorship order following acceptance may be considered, but only in special circumstances.
Q. Do my co-authors need to create an OpenReview account?
A. YES. Before the submission deadline, every co-author needs to create (or update) an OpenReview profile. The information entered in the profile is used for conflict resolution.
Q. Do the 2-pages include the reference?
A. NO, the 2-pages is only for the contents of the paper. References can go beyond the 2-pages.
Q. Can I have an appendix after the 2-pages?
A. NO. The objective of the extended abstract is to summarize research that is not ready for publication, or that was published already.
Q. Are acknowledgements permitted in the submitted paper?
A. Yes. But remember that the paper is non-archival and won't be made public after the review.
Q. Can I link to an external webpage from my submission?
A. No. This is strongly discouraged because it runs a high risk of circumventing length or deadline restrictions.
Q. I need to insert the number of the paper in the template. How can I get it?
A. You should create a submission on OpenReview. There you will see the number assigned to your paper.
Q. I want to present a published work, can I add new authors?
A. NO. The authors of an abstract for a published work must be a subset of the original paper authors.
Q. Can I submit the original paper as is?
A. NO. The objective of the extended abstract is to summarize the research for evaluation.
Q. Can I submit a revised version of the paper?
A. No. There will be a round of reviews and then decisions will be made. The extended abstracts are not archived.
Q. Is there an author-reviewer discussion period?
A. No.
Q. What is the LLM Policy for authors?
A. Authors may use any tools they find productive in preparing a paper, but must be aware that they are responsible for any misrepresentation, factual inaccuracy or plagiarism in their paper. Papers containing citations of non-existent material will be rejected when found, and may be rejected without review. Similarly, papers containing obvious factual inaccuracies will be rejected when found and may be rejected without review. It is not a defense to a charge of plagiarism or of inaccuracy to argue that “an LLM did it”. You are responsible for what you submit.
Q. How will the LLM policy be implemented?
A. Referees who find inaccuracies should act as they usually would; as should Area Chairs. Glaring examples of citations to non-existent material can be desk-rejected.
Q. What is the LLM Policy for reviewers?
A. Reviewers may use any device, including an LLM, to polish their review wording, but must vouch for, and be responsible for, the accuracy of the review. It is a significant act of reviewer misconduct to allow an LLM to see a submission. PCs interpret showing a submission to an LLM as a deliberate reviewer violation of confidentiality. The PCs reserve the right to report reviewer misconduct to other future machine learning and related conferences. These conferences then may take actions, e.g., there was a recent PAMI-TC vote that CVPR reviewer misconduct may lead to a 2-year submission ban.
Q. What is the reasoning behind the LLM policy?
A. The action that most likely affects the credibility of the conference is using an LLM to write the summary of the paper. The summary is a necessary part of reviewing, because it compels the reviewer to show what they think the paper is about, and so validates the review. A summary that has been polished by an LLM which hasn’t seen the paper is acceptable, as long as the referee vouches for the review. A summary that has been prepared by an LLM—so one where the LLM sees the paper—is profoundly damaging, because it may allow a review to be prepared without the referee trying to understand the paper.
Q. How will the LLM policy be implemented?
A. An author may complain to their AC that a summary (and/or other parts of the review) have been prepared by an LLM that has seen the paper. Such a complaint would need to be supported by an example summary (or other part of the review) prepared by the author giving the paper to an LLM. If this matches the reviewer’s comments sufficiently, ACs will pass the complaint on to PCs who are then entitled, but not required, to act. Complaints must be submitted on a separate confidential comment. PCs strongly discourage frivolous complaints. Authors should be aware that a complaint to an AC about a review prepared by an LLM without reasonable evidence in support of that complaint, is wasting the ACs time.