Keynote: Unveiling the Linguistic Weaknesses of Neural MT

UNVEILING: What Makes Linguistics Olympiad Puzzles Tricky for LLMs?

Large language models (LLMs) have demonstrated potential in reasoning tasks, but their performance on linguistics puzzles remains consistently poor. These puzzles, often derived from Linguistics Olympiad (LO) contests, p…

NormEnsembleXAI: Unveiling the Strengths and Weaknesses of XAI Ensemble Techniques

This paper presents a comprehensive comparative analysis of explainable artificial intelligence (XAI) ensembling methods. Our research brings three significant contributions. Firstly, we introduce a novel ensembling meth…

Keynote Abstract: Current Open Questions for Operational Event Data

In this brief keynote, I will address what I see as five majorissues in terms of development for operational event datasets (that is, event data intended for real time monitoringand forecasting, rather than purely for ac…

Agility in Software 2.0 -- Notebook Interfaces and MLOps with Buttresses and Rebars

Artificial intelligence through machine learning is increasingly used in the digital society. Solutions based on machine learning bring both great opportunities, thus coined "Software 2.0," but also great challenges for …

Keynote: Language Adaptation