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

Website: 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.

Important Dates

• First call for papers: May 21, 2026
• Submission deadline: August 7, 2026 (Friday)
• Submission of already pre-reviewed ARR papers: TBD
• Notification of acceptance: TBD
• Camera-ready papers due: TBD
• Workshop date: October 24 - 29, 2026 (workshop date TBD)

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

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 by August 7, 2026 (Friday) 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, submitted electronically via OpenReview and should follow the EMNLP 2026 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 TBD. 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 EMNLP 2026 formatting guidelines (following the ARR CfP: use the official ACL style templates, which are available here).

All submissions are archival, but 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.

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.