Submissions on easychair.
Submissions are made in two stages, a submission of a preliminary abstract later followed by a submission of the paper itself. Papers must present original, unpublished research and implementation results. Simultaneous submissions to FSMNLP and to another conference or workshop are allowed. According to the ACL double submission policy, doubly-submitted papers should indicate this fact on the title page. If accepted at both FSMNLP and the other meeting, such a paper must be withdrawn from one of them. Withdrawal from FSMNLP shall be as soon as possible but no later than one week after the notification of acceptance at FSMNLP.
FSMNLP accepts two kinds of submissions:
- long papers (8 pages excluding references) reporting completed, significant research,
- short papers (4 pages excluding references) reporting ongoing work and partial results, implementations, grammars, practical tools, interactive software demos, etc.
Short papers are expected to be presented as system demos, posters and/or short presentations, while long papers are presented in full talks.
All submissions are electronic and in PDF format via a web-based submission server. Authors are strongly encouraged to preparte their papers in LaTeX using the ACL 2021-12 style files to produce the PDF document. The zip archive of the style files can be downloaded here.
Information about the author(s) and other identifying information such as obvious self-references (e.g., “We showed in [12] …”) and financial or personal acknowledgements should be omitted in the submitted papers whenever feasible. You may not make a non-anonymized version of your paper available online to the general community (for example, via a preprint server) during the anonymity period. Versions of the paper include papers having essentially the same scientific content but possibly differing in minor details (including title and structure) and/or in length.
Papers must be submitted electronically in PDF on easychair
A paper may contain a clearly marked appendix and data files to support its claims. This material will not be published. While reviewers are urged to consult this extra material for better comprehension, it is at their discretion whether they do so. Such extra material should also be anonymized to the extent feasible.