Full papers
Up to 8 pages for substantial contributions.
NLP/CORE Unranked
UncertaiNLP2026 ARR Commitment 2026
Third Workshop on Uncertainty-Aware NLP @ EMNLP 2026 -- ARR Commitment
The UncertaiNLP 2026 workshop, co-located with EMNLP 2026 in Budapest, brings together researchers focused on uncertainty in human language and NLP systems, including LLMs. It aims to advance research that embraces linguistic ambiguity and models uncertainty through formal, computational, and evaluative approaches, with a special emphasis on hallucinations, calibration, and probabilistic methods.
Key deadlines
Verified September 9, 2026Full paper
August 24, 2026
AoE
Workshop timeline
Submission and decisions
Full paperKey deadline
August 24, 2026 · AoE
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Short papers
Up to 4 pages for ongoing or preliminary work.
Research areas in scope
01
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)
02
Learning (or parameter estimation)
Learning from single and/or multiple referencesGradient estimation in latent variable modelsProbabilistic inferenceTheoretical and applied work on approximate inference (e.g., variational inference, Langevin dynamics)Unbiased and asymptotically unbiased sampling algorithms
03
Decision making
Utility-aware decoders and controllable generationSelective predictionActive learning
04
Evaluation
Statistical evaluation of language modelsCalibration to interpretable notions of uncertainty (e.g., calibration error, conformal prediction)Evaluation of epistemic uncertainty
05
Hallucinations
Theoretical and empirical study of hallucination phenomena in NLU/NLGDescribing, formalising, categorising hallucination phenomenaMethods for detecting and quantifying hallucinationsMitigation techniques including uncertainty-aware generation, retrieval-augmented methods, and controllable generationRelationship between specific kinds (or sources) of uncertainty and hallucination occurrence
06
Formal and theoretical foundations
Formal tools for uncertainty representationTheoretical work on probability and its generalizationsSymbolic representations of uncertaintyDocumenting sources of uncertaintyTheoretical underpinnings of linguistic sources of variationData collection (e.g., to document linguistic variability, multiple perspectives, etc.)
Policies worth checking twice
- Submissions must be in PDF format and follow EMNLP 2026 formatting guidelines using official ACL style templates.
- Three submission types are accepted: direct archival, direct non-archival, and ARR commitment.
- ARR commitment submissions must have existing ACL Rolling Review (ARR) reviews and be linked via OpenReview; EMNLP industry track reviews are not accepted.
- Non-archival submissions can be concurrently submitted to EMNLP 2026 (including industry track) but not to other EMNLP co-located workshops.
- Accepted archival papers may use one additional page for camera-ready versions to address reviewer comments.
- Every direct submission must appoint one or more eligible authors for reciprocal reviews (standard load: 3 papers).
- Reciprocal reviewers must hold a PhD or have co-authored at least one peer-reviewed paper at ACL, EMNLP, NAACL, EACL, COLING, NeurIPS, ICML, ICLR, AAAI, IJCAI, or comparable venues.
- Failure to complete reciprocal reviews results in desk rejection.
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026