Abstracts
Short submissions for presentation at the workshop; accepted abstracts grant presentation rights.
NLP/CORE Unranked
CLUG-EVAS 2026
2nd Workshop on Artificial Cultural Reasoning: Cross- Border Language Processing & Empirical Validation
The CLUG-EVAS 2026 workshop focuses on empirical validation of cultural reasoning in AI within the multilingual SaarLorLux region, combining the CLUG project's culturally annotated multilingual benchmarks with EVAS's ecological validation framework to test whether language models can authentically represent cross-border cultural and linguistic nuances. It brings together researchers from linguistics, computer science, sociology, and related fields to discuss how cultural meaning survives or collapses in AI-generated and translated text.
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Papers
Full papers up to 8 pages following ACL formatting guidelines; accepted papers may be invited to submit to a related Special Issue.
Research areas in scope
01
Workshop Topics
Multi-Dimensional Evaluation: Applications, adaptations, or extensions of annotation frameworks (for cross-border language processing)Empirical Validation: Novel metrics, datasets, and human/machine evaluation pipelines for stress-testing cross-cultural & cross-border reasoningCross-Border Processing: How culturally embedded meaning survives or collapses in LLM translation and generation across LB/FR/DE/ENEcological Validity & Bias: Testing whether surface fluency masks behavioral, pragmatic, or cultural failure in real-world, multilingual contexts
Policies worth checking twice
- Submissions must follow ACL formatting guidelines.
- Submissions are limited to 8 pages.
- Submission is via OpenReview.net.
- Acceptance of a paper grants presentation rights at the workshop.
- Final publication in the associated Special Issue requires post-workshop peer review and is not guaranteed by workshop acceptance.
- Participation is free but mandatory registration is required.
- No prior expertise in NLP or AI evaluation is required.
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026