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Welcome to the website of the UncertaiNLP workshop to be held at EACL 2024 in Malta.

Tagline: UncertaiNLP brings together researchers embracing sources of uncertainty from human language and NLP tools; harnessing them for improved NLP.

Important Dates

All deadlines are 11:59pm UTC-12 (“anywhere on earth”).

Workshop Topic and Content

Human languages are inherently ambiguous and understanding language input is subject to interpretation and complex contextual dependencies. Nevertheless, the main body of research in NLP is still based on the assumption that ambiguities and other types of underspecification can and have to be re-solved. This workshop will provide a platform for research that embraces variability in human language and aims to represent and evaluate the uncertainty that arises from it, and from modeling tools themselves.

Workshop Topics

UncertaiNLP welcomes submissions to topics related (but not limited) to:

Workshop Schedule

The workshop will take place March 22, 2024 at the Bastion 2 room of the Corinthia St George’s Bay hotel. The detailed program is available here and an overview of the schedule is given below:

Invited Speakers

Kristin Lennox Clara Meister Chrysoula Zerva
Kristin Lennox (Exponent, US)
Clara Meister (ETH Zürich, Switzerland)
Chrysoula Zerva (Instituto Superior Tecnico, Portugal)

Kristin Lennox is a consultant at Exponent with more than ten years of experience applying statistics, machine learning, and operations research techniques to scientific and engineering problems. Dr. Lennox received her Ph.D. in statistics from Texas A&M University in 2010. She then joined Lawrence Livermore National Laboratory, where she cofounded and served as the first director of their internal statistical consulting service. After leaving the laboratory she spent several years in the software industry with a focus on AI in industrial settings, and she currently serves as a consultant regarding statistics and AI implementation for applications in many areas, including environmental science, automotive and consumer product risk, and software. Her expertise includes experimental design, analysis of computer experiments, and risk assessment in high consequence environments. Dr. Lennox’s recent professional experience has focused on methods to characterize safety benefits of advanced driver assistance systems (ADAS) and automated driving. Dr. Lennox is passionate about statistics and AI education and has created a series of videos for technical and lay audiences on these topics.

Clara Meister is a PhD student in Computer Science with Prof. Ryan Cotterell at ETH Zürich, supported by a Google PhD Fellowship. She is passionate about the general application of statistics and information theory to natural language processing. A large portion of her research in the last years has been on natural language generation—specifically, on decoding methods for probabilistic models. Her additional interests within the field of natural language generation include evaluation metrics and the incorporation of uncertainty into decoding methods.

Chrysoula (Chryssa) Zerva is an Assistant Professor in Artificial Intelligence at the Instituto Superior Tecnico in Lisbon, Portugal. She is also a member of LUMLIS, the Lisbon ELLIS unit. She obtained her Ph.D. in 2019 from the University of Manchester working on “Automated identification of textual uncertainty” under the supervision of Prof. Sophia Ananiadou. She was subsequently awarded the EPSRC doctoral prize fellowship to study (mis)information propagation in health and science. In 2021, she joined the Instituto de Telecomunicações in Lisbon as a post-doc for the DeepSPIN project under the supervision of Prof. André Martins and worked on a range of machine learning and NLP related topics including uncertainty quantification, machine translation and quality estimation. Beyond core research, she is interested in dissemination of science to the public and keen on promoting women’s participation in research and science; she has previously presented in or co-organised events such as the Pint of Science, Women in Localisation and Greek Girls Code.

Call for Papers

Authors are invited to submit by December 18, 2023 original and unpublished research papers in the following categories:

All submissions must be in PDF format, submitted electronically via OpenReview and should follow the EACL 2024 formatting guidelines (following the ARR CfP: use the official ACL style templates, which are available here).

We now accept submissions with already existing ACL Rolling Reviews (ARR) via OpenReview, with the deadline January 18 AoE. These submissions must have been reviewed by ARR before, which will be used in our evaluation, and which must be linked to our system through the paper link field available in the OpenReview form. Please make sure to also follow the EACL 2024 formatting guidelines (following the ARR CfP: use the official ACL style templates, which are available here).

We also invite authors of papers accepted to Findings to reach out to the organizing committee of UncertaiNLP to present their papers at the workshop, if in line with the topics described above.

Camera-ready versions for accepted archival papers should be uploaded to the submission system by the camera-ready deadline. Authors may use up to one (1) additional page to address reviewer comments.

Call for Papers is available here.

Program Committee

Workshop Organizers

Wilker Aziz, University of Amsterdam
Joris Baan, University of Amsterdam
Hande Celikkanat, University of Helsinki
Marie-Catherine de Marneffe, UCLouvain and FNRS


Barbara Plank, LMU Munich and IT University of Copenhagen
Swabha Swayamdipta, USC Viterbi CS
Jörg Tiedemann, University of Helsinki
Dennis Ulmer, IT University of Copenhagen

Contact

You can contact the organizers by email to uncertainlp@googlegroups.com.

Anti-Harassment Policy

UncertaiNLP workshop adheres to the ACL’s code of ethics, ACL’s anti-harassment policy , and ACL’s code of conduct.

Image Credits

Images were created using text-to-image model supplied via getimg.ai/, using the CreativeML Open Rail-M license.