6 citations · 6 across the 9 of their papers we have counts for
10 papers
How to Evaluate When You Don't Know How to Evaluate? Choosing Reliable Setups for Base Language Model Benchmarking
Shenbin Qian, David Samuel, Jindřich Helcl +2
Evaluation of large language models (LLMs) remains largely pre-scientific: it involves many design decisions, with little guidance on how to make them. These choices can substantia…
MultiSynt/MT: Trillion-Token Multi-Parallel Pre-Training Data Translated Across 36 Languages
Maximilian Idahl, Jörg Tiedemann, Sampo Pyysalo +19
Open web-scale pre-training corpora remain concentrated in English, limiting multilingual LLM development. We introduce MultiSynt/MT, an open synthetic parallel corpus with approxi…
DHPLT: large-scale multilingual diachronic corpora and word representations for semantic change modelling
Mariia Fedorova, Andrey Kutuzov, Khonzoda Umarova
In this resource paper, we present DHPLT, an open collection of diachronic corpora in 41 diverse languages. DHPLT is based on the web-crawled HPLT datasets; we use web crawl timest…
HPLT 3.0: Very Large-Scale Multilingual Resources for LLMs and MT. Mono- and Bi-lingual Data, Multilingual Evaluation, and Pre-Trained Models
Stephan Oepen, Nikolay Arefev, Mikko Aulamo +29
We present an ongoing initiative to provide open, very large, high-quality, and richly annotated textual datasets for almost 200 languages. At 30 trillion tokens, this is likely th…
Explaining novel senses using definition generation with open language models
Mariia Fedorova, Andrey Kutuzov, Francesco Periti +1
We apply definition generators based on open-weights large language models to the task of creating explanations of novel senses, taking target word usages as an input. To this end,…
An Expanded Massive Multilingual Dataset for High-Performance Language Technologies (HPLT)
Laurie Burchell, Ona de Gibert, Nikolay Arefyev +32
Training state-of-the-art large language models requires vast amounts of clean and diverse textual data. However, building suitable multilingual datasets remains a challenge. In th…
Definition generation for lexical semantic change detection
Mariia Fedorova, Andrey Kutuzov, Yves Scherrer
We use contextualized word definitions generated by large language models as semantic representations in the task of diachronic lexical semantic change detection (LSCD). In short,…
AXOLOTL'24 Shared Task on Multilingual Explainable Semantic Change Modeling
Mariia Fedorova, Timothee Mickus, Niko Partanen +3
This paper describes the organization and findings of AXOLOTL'24, the first multilingual explainable semantic change modeling shared task. We present new sense-annotated diachronic…
Enriching Word Usage Graphs with Cluster Definitions
Mariia Fedorova, Andrey Kutuzov, Nikolay Arefyev +1
We present a dataset of word usage graphs (WUGs), where the existing WUGs for multiple languages are enriched with cluster labels functioning as sense definitions. They are generat…
A New Massive Multilingual Dataset for High-Performance Language Technologies
Ona de Gibert, Graeme Nail, Nikolay Arefyev +10
We present the HPLT (High Performance Language Technologies) language resources, a new massive multilingual dataset including both monolingual and bilingual corpora extracted from…