Call for Papers

Important Dates

• Submission Begins:
  • Submission Portal: OpenReview
• Submission Deadline: Aug 15, 2024 Aug 28, 2024 (11:59pm, anywhere on earth)
• Notification of Acceptance: Sep 30, 2024 Oct 4, 2024
• Camera-ready papers due: Oct 7 (11:59pm, anywhere on earth)
• Workshop Date: Sat, Nov 16 co-located with EMNLP 2024 in November, Miami

EMNLP Findings Papers: If you would like to present your findings paper as a poster at our workshop, please email us at customnlp4u@gmail.com by October 20th. In your email, please include the following details: the title, abstract, a link to the paper, and a brief explanation of how the paper fits with the theme of our workshop.

Topics of Interest

For NLP models to be usable in practice, particularly in emerging scenarios with widely varying use cases, situations, and user expectations, there is a need to develop models that can be tailored to different consumers (individuals, groups, or organizations) and easily controlled by them; models that can reason about their users’ (often private) knowledge and context to provide personalized responses. The topics of this workshop include (but not limited to):

• Data: Data collection, processing, analysis, and annotation efforts to increase representation and aid customization; discussion and analysis of data sources not publicly available, and associated issues of privacy and copyright.
• Modeling: New pretraining, fine-tuning, inference methods for customizing NLP models; customizing reward models and model alignment to diverse consumers. New modeling paradigms aimed at customization such as model ensembles, model averaging, federated learning, nonparametric models, etc.; customizing models at inference time via prompting, in-context learning, chain-of-thought prompting, etc.
• Evaluation: Evaluation of existing generalist, non-customized models, identifying their shortcomings for varied use-cases; evaluation of customization techniques and customized models; interpretability and analysis of customization patterns across different kinds of consumers.
• Open Science: Best practices for open and reproducible science concerning customizable NLP: dataset release and licensing, open-sourcing models, related privacy, copyright, and policy issues.
• Applications: e.g., information seeking on sensitive data comprising legal, medical, or financial information; NLP models for communities reflecting sociolects, dialects, or other language varieties; personalized AI assistants, etc.
• Ethical Issues: privacy and copyright; personalization, intrusiveness, unintended biases; invisibility versus hypervisibility.

Guidelines

• Our author guidelines follow the ARR requirements unless otherwise specified.
• Paper submission is hosted on OpenReview.
• We welcome both short (up to 4 pages) and long papers (up to 8 pages), not including references or appendix.
  • Please use the provided LaTex template (Overleaf) for your submission. Please follow the paper formatting guidelines general to “*ACL” conferences as specified in the style files. Authors may not modify the style files or use templates designed for other conferences.
  • The paper should be anonymized and uploaded to OpenReview as a single PDF.
  • You may use as many pages of references and appendix as you wish, but reviewers are not required to read the appendix.
  • Posting papers on preprint servers like ArXiv is permitted.
  • We encourage each submission to discuss the ethical and societal implications of their work, wherever applicable.
• This workshop offers both archival and non-archival options for submissions. Archival papers will be indexed with proceedings, while non-archival submissions will not.
• The review process will be double-blind.
  

Organizers

Steering Committee