CfP: UserNLP @ The Web Conference 2022 - 1st Workshop on User-Centered NLP

1st Workshop on User-Centered NLP

Workshop date: April 26, 2022

Workshop website: https://caisa.informatik.uni-marburg.de/user_nlp.html

Contact email: user-centered-nlp-/[email protected]
Important Dates

   -

   February 3rd - Submissions Due
   -

   March 3rd - Notification of Acceptance
   -

   April 26th - Workshop Date (online)


All the deadlines are 11:59 PM GMT -12.
Workshop Description

The 1st User-Centered NLP Workshop will be held in conjunction with the Web
Conference (WWW) 2022 virtually in Lyon, France.

Current NLP models are mostly trained as "one-size-fits-all", i.e. without
explicitly consideration of the diversity in the use and interpretation of
language among individuals or groups of individuals. Such user-level
variation (delineated by, e.g., demographics, culture, user interests) can
cause stylistic and even semantic disparities, which decrease dialogue
coherence, harm fairness, and reduce model robustness. User-centered NLP
can fill these gaps by explicitly taking these variations into account and
focusing on user-level modeling tasks.

We aim to create a platform where researchers can present rising challenges
in building user-centered NLP models. While we have data statement
discussions and schema for document-level annotations, few studies have
explored data schema and standards on the user-level. Moreover,
conventional evaluation metrics and schemes for the document-level models
may not be appropriate to capture the diversity and complexity of
user-level information. The lack of ethically appropriate, standardized,
and easily accessible evaluation data and metrics is perhaps the major
hindrance to the development of this field, impeding the reproducibility of
experimental results. Finally, user-centered NLP raises a wide range of
important ethical questions, such as algorithmic fairness and user privacy.
An informed discussion on these timely topics requires gathering at one
table researchers who encounter stylistic disparities and user-level tasks
directly or indirectly in their work.

The overarching questions that motivate this workshop are:

   1.

   To what extent do stylistic variations indirectly impact downstream
   applications which were historically treated as stylistically uniform?
   2.

   To what extent is it desirable to exploit individual variations to
   reduce demographic disparity, promote user-level models and personalize NLP
   applications?
   3.

   To what extent recent advances in related areas including representation
   learning, domain adaptation and transfer learning can leverage individual
   variations, understand user intentions, customize NLP models, and deliver
   interpretable outputs for users’ specific needs?
   4.

   How to better evaluate user-centric models to shed insight on user-level
   disparities and the impact of personalized models?
   5.

   How to better achieve privacy-preserving user centric NLP models when it
   comes to a wide range of personalization and user level tasks?
   6.

   How much user data is sufficient for the desired system performance?

A non-exhaustive list of proposed topics and applications of interest
follows. Suggested topics include:

   -

   Effects of stylistic variation on downstream tasks
   -

   User-level distributional vector models
   -

   Personalization and user-aware natural language generation
   -

   Fairness and ethics in user-level tasks
   -

   User modeling and user behavior analysis
   -

   Effective approaches to evaluate user-level models
   -

   Interactive and personalized information retrieval
   -

   Challenges in user privacy and private user-centered models

Potential applications include:

   -

   User sociodemographic inference applications, together with their issues
   and risks
   -

   Personalized text generation
   -

   User modeling for health applications (e.g. mental health, preventive
   care)
   -

   Identifying trustworthiness and deception of users
   -

   Rhetoric and personalization (e.g. stylistic choices in political
   speeches, etc.)

Submission Guidelines:

   -

   Full research papers (up to 8 pages for main content)
   -

   Short research papers (up to 4 pages for main content)
   -

   Vision/Position papers (up to 4 pages for main content)



The workshop calls for full research papers (up to 8 pages + 2 pages of
appendices + 2 pages of references), describing original work on the listed
topics, and short papers (up to 4 pages + 2 pages of appendices + 2 pages
of references), on early research results, new results on previously
published works, demos, and projects. In accordance with Open Science
principles, research papers may also be in the form of data papers and
software papers (short or long papers). The former present the motivation
and methodology behind the creation of data sets that are of value to the
community; e.g., annotated corpora, benchmark collections, training sets.
The latter presents software functionality, its value for the community,
and its application to a non-specialist reader. To enable reproducibility
and peer-review, authors will be requested to share the DOIs of the data
sets and the software products described in the articles and thoroughly
describe their construction and reuse.



The workshop will also call for vision/position papers (up to 4 pages + 2
pages of appendices + 2 pages of references) providing insights towards new
or emerging areas, innovative or risky approaches, or emerging applications
that will require extensions to the state of the art. These do not have to
include results already, but should carefully elaborate on the motivation
and the ongoing challenges of the described area.



Submissions for review must be in PDF format and must adhere to the ACM
template and format. Submissions that do not follow these guidelines, or do
not view or print properly, may be rejected without review.



The proceedings of the workshops will be published jointly with The Web
Conference 2022 proceedings.



Submit your contributions following the link:
<https://sci-k.github.io/2022/#submission>
https://easychair.org/cfp/UserNLP_2022

The deadline for submission is 11:59pm GMT -12 on Feb, 3rd, 2022.
Reviewing Procedure

Submissions will be peer reviewed in the double-blind format and evaluated
on relevance to the community. The presentation format (talk or poster)
will be decided based on scientific merit and potential interest to a broad
audience.
Multiple-Submission Policy

Papers to appear in the workshop proceedings have to contain a creative and
original work, which was not submitted elsewhere. You are allowed to submit
an already submitted paper in case you are only interested in a
non-archival presentation of your work. This, however, has to be clearly
indicated at submission time.
Organising Committee

Xiaolei Huang, University of Memphis

Lucie Flek, University of Marburg

Silvio Amir, Northeastern University

Diyi Yang, Georgia Tech

Charles Welch, University of Marburg

Ramit Sawhney, ShareChat AI

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