Nodes drift and rewire; a node fires once two of its neighbours have fired within a short window, then falls into a refractory pause. Cascades either die out or sweep the graph. Inspired by my PhD work on bootstrap percolation with inhibition.
Click to ignite · hold to widen the ignition front
Hafsteinn
Einarsson
Associate Professor, University of Iceland
Principal Scientist, Amgen deCODE
I lead a research group working on natural language processing for Icelandic and Faroese, with active projects in computer vision for the natural sciences, clinical AI, and human genetics.
News
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Group presenting seven papers at LREC 2026 in Palma de Mallorca.
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New paper on temporal vision-language features for fish classification (Ecological Informatics).
Selected publications
NLP for Icelandic & Germanic MazeEval: a benchmark for testing sequential decision-making in language models Einarsson, H. · Proceedings of the fifteenth language resources and evaluation conference (LREC 2026) · 2026
MazeEval is a benchmark for testing sequential decision-making in language models through navigation tasks in procedurally generated mazes. The setup probes whether models can maintain a coherent internal map across multiple turns of interaction rather than relying on local pattern matching. Single-author paper published at LREC 2026.
NLP for Icelandic & Germanic Curated retrieval versus open web search in public AI information services: a coverage-trust trade-off Einarsson, H., Einarsson, H. B., Ólafsson, J. G., Þorsteinsson, J. G. · arXiv preprint arXiv:2607.05217 · 2026
A pre-launch expert evaluation of Evrópuvefur, a government-funded University of Iceland service that answers questions about the European Union, conducted as Iceland prepared for its August 2026 referendum on resuming EU accession talks. Five domain experts produced 551 evaluations of 449 AI-generated answers, comparing a curated local corpus (RAG) against open web search: web search answered more questions but flagged an untrustworthy or irrelevant source in 35% of answers, while the curated corpus was trustworthy yet limited in coverage. Argues that source trustworthiness is a measurable but largely invisible dimension of information quality in public AI services. First-author arXiv preprint.
Machine Learning · Natural Sciences Temporal aggregation of vision-language features for high-accuracy fish classification in automated monitoring Silva Martins, J. R., Bárðarson, H., Guðbrandsson, J., Einarsson, H. · Ecological Informatics · 2025
Aggregates temporal vision-language features from underwater video to classify fish species in automated monitoring streams, combining per-frame embeddings with temporal pooling to handle the noise and occlusion that limit frame-by-frame classifiers in deployed systems. Published in Ecological Informatics (2025) as part of the lab's ongoing computer-vision work with the Marine and Freshwater Research Institute.