Search Results for author: Hafsteinn Einarsson

Found 7 papers, 0 papers with code

Fictionary-Based Games for Language Resource Creation

no code implementations NIDCP (LREC) 2022 Steinunn Rut Friðriksdóttir, Hafsteinn Einarsson

In this paper, we present a novel approach to data collection for natural language processing (NLP), linguistic research and lexicographic work.

Natural Questions in Icelandic

no code implementations LREC 2022 Vésteinn Snæbjarnarson, Hafsteinn Einarsson

The dataset is a valuable resource for Icelandic which we demonstrate by creating and evaluating a system capable of extractive QA in Icelandic.

Extractive Question-Answering Natural Questions +1

Cross-Lingual QA as a Stepping Stone for Monolingual Open QA in Icelandic

no code implementations NAACL (MIA) 2022 Vésteinn Snæbjarnarson, Hafsteinn Einarsson

Our approach requires only limited QA resources in the given language, along with machine-translated data, and at least a bilingual language model.

Language Modelling Open-Ended Question Answering

Building an Icelandic Entity Linking Corpus

no code implementations DCLRL (LREC) 2022 Steinunn Rut Friðriksdóttir, Valdimar Ágúst Eggertsson, Benedikt Geir Jóhannesson, Hjalti Daníelsson, Hrafn Loftsson, Hafsteinn Einarsson

We describe our approach of using a multilingual entity linking model (mGENRE) in combination with Wikipedia API Search (WAPIS) to label our data and compare it to an approach using WAPIS only.

Entity Linking

A Warm Start and a Clean Crawled Corpus -- A Recipe for Good Language Models

no code implementations14 Jan 2022 Vésteinn Snæbjarnarson, Haukur Barri Símonarson, Pétur Orri Ragnarsson, Svanhvít Lilja Ingólfsdóttir, Haukur Páll Jónsson, Vilhjálmur Þorsteinsson, Hafsteinn Einarsson

To train the models we introduce a new corpus of Icelandic text, the Icelandic Common Crawl Corpus (IC3), a collection of high quality texts found online by targeting the Icelandic top-level-domain (TLD).

Constituency Parsing Grammatical Error Detection +4

The linear hidden subset problem for the (1+1) EA with scheduled and adaptive mutation rates

no code implementations16 Aug 2018 Hafsteinn Einarsson, Marcelo Matheus Gauy, Johannes Lengler, Florian Meier, Asier Mujika, Angelika Steger, Felix Weissenberger

For the first setup, we give a schedule that achieves a runtime of $(1\pm o(1))\beta n \ln n$, where $\beta \approx 3. 552$, which is an asymptotic improvement over the runtime of the static setup.

Evolutionary Algorithms

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