Call for papers: UncertaiNLP - Third Workshop on Uncertainty-Aware NLP @ EMNLP 2026

Website (incl. important dates): https://uncertainlp.github.io/

We invite submissions to the third edition of the UncertaiNLP workshop on Uncertainty-Aware NLP, to be held at EMNLP 2026.

Introduction

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 resolved. 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 the modeling tools themselves.

Topics of Interest

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

• Formal tools for uncertainty representation
  • Theoretical work on probability and its generalizations
  • Symbolic representations of uncertainty
• Documenting sources of uncertainty
  • Theoretical underpinnings of linguistic sources of variation
  • Data collection (e.g., to document linguistic variability, multiple perspectives, etc.)
• Modeling
  • Explicit representation of model uncertainty (e.g., parameter and/or hypothesis uncertainty, Bayesian NNs in NLU/NLG, verbalised uncertainty, feature density, external calibration modules)
  • Disentangled representation of different sources of uncertainty (e.g., hierarchical models, prompting)
  • Reducing uncertainty due to additional context (e.g. clarification questions, retrieval/API augmented models)
• Learning (or parameter estimation)
  • Learning from single and/or multiple references
  • Gradient estimation in latent variable models
• Probabilistic inference
  • Theoretical and applied work on approximate inference (e.g., variational inference, Langevin dynamics)
  • Unbiased and asymptotically unbiased sampling algorithms
• Decision making
  • Utility-aware decoders and controllable generation
  • Selective prediction
  • Active learning
• Evaluation
  • Statistical evaluation of language models
  • Calibration to interpretable notions of uncertainty (e.g., calibration error, conformal prediction)
  • Evaluation of epistemic uncertainty
• Hallucinations
  • Theoretical and empirical study of hallucination phenomena in NLU/NLG
  • Describing, formalising, categorising hallucination phenomena
  • Methods for detecting and quantifying hallucinations
  • Mitigation techniques including uncertainty-aware generation, retrieval-augmented methods, and controllable generation
  • Relationship between specific kinds (or sources) of uncertainty and hallucination occurrence

Submission Guidelines

Authors are invited to submit original and unpublished research papers in the following categories:

• Full papers (up to 8 pages) for substantial contributions.
• Short papers (up to 4 pages) for ongoing or preliminary work.

All submissions must be in PDF format and should follow the EMNLP 2026 formatting guidelines (following the ARR CfP: use the official ACL style templates, which are available here).

We accept three types of submissions:

1. Direct archival submissions. Original and unpublished papers submitted directly to the workshop via OpenReview. Submissions will be reviewed by the workshop program committee and, if accepted, will be published in the workshop proceedings.

2. Direct non-archival submissions. Papers submitted directly to the workshop via the same OpenReview link. Non-archival submissions go through the same review process as archival ones and, if accepted, are presented at the workshop, but they are not included in the workshop proceedings. This option allows authors to receive feedback and present their work at the workshop while retaining the possibility of submitting it to another venue later. Please indicate in the submission form that your submission is non-archival.

3. ARR commitment. Submissions with already existing ACL Rolling Review (ARR) reviews, committed via OpenReview, with the deadline of August 23, 2026. These submissions must have been reviewed by ARR before; the ARR reviews will be used in our evaluation and must be linked to our system through the paper link field available in the OpenReview form. This route is also open to papers already accepted to EMNLP 2026 (main conference or Findings): if your work fits the topics above, we warmly invite you to commit your ARR reviews and present it at the workshop as well — our goal is to gather the community working on uncertainty quantification in one place. Please note that committing your reviews does not automatically guarantee presentation at the workshop: the organizers will make the final selection based on workshop relevance, EMNLP acceptance status, ARR reviews and scores, and available capacity. Note that only ARR reviews can be committed: reviews from the EMNLP 2026 industry track are not accepted, so if your paper was reviewed there, please submit it directly via the regular submission form as a non-archival submission instead.

Concurrent submissions. Non-archival submissions can be simultaneously submitted to EMNLP 2026 (including industry track), but not to EMNLP co-located workshops.

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.

Reciprocal Reviewing

To ensure a high-quality review process, every direct submission must appoint (via the submission form) one or more authors responsible for reciprocal reviews (standard load: 3 papers). Reciprocal reviewers must meet both eligibility criteria:

• hold a PhD or
• have co-authored at least 1 peer-reviewed paper at venues such as ACL, EMNLP, NAACL, EACL, COLING, NeurIPS, ICML, ICLR, AAAI, IJCAI, or comparable venues

Only submissions with no eligible authors are exempt. Failure to complete reciprocal reviews by the announced deadline will result in desk rejection of the associated submission (exceptions are rare and assessed independently by the workshop chairs).

Workshop Organizers

• Wilker Aziz, University of Amsterdam
• Jonathan Berant, Tel Aviv University and Google Deepmind
• Bryan Eikema, University of Amsterdam
• Marie-Catherine de Marneffe, UCLouvain and FNRS
• Barbara Plank, LMU Münich and IT University of Copenhagen
• Artem Shelmanov, Mohamed bin Zayed University of Artificial Intelligence
• Swabha Swayamdipta, USC Viterbi CS
• Jörg Tiedemann, University of Helsinki
• Artem Vazhentsev, Mohamed bin Zayed University of Artificial Intelligence
• Raúl Vázquez University of Helsinki
• Chrysoula Zerva, Instituto de Telecomunicações

Program Committee

A list of program committee members will be available on the workshop website.

Contact

For inquiries, please contact uncertainlp@googlegroups.com.