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Systematic Generalization in Language Models Scales with Information Entropy
Sondre Wold, Lucas Georges Gabriel Charpentier, Étienne Simon
Systematic generalization remains challenging for current language models, which are known to be both sensitive to semantically similar permutations of the input and to struggle wi…
Compositional Generalization with Grounded Language Models
Sondre Wold, Étienne Simon, Lucas Georges Gabriel Charpentier +3
Grounded language models use external sources of information, such as knowledge graphs, to meet some of the general challenges associated with pre-training. By extending previous w…
More Room for Language: Investigating the Effect of Retrieval on Language Models
David Samuel, Lucas Georges Gabriel Charpentier, Sondre Wold
Retrieval-augmented language models pose a promising alternative to standard language modeling. During pretraining, these models search in a corpus of documents for contextually re…
Estimating Lexical Complexity from Document-Level Distributions
Sondre Wold, Petter Mæhlum, Oddbjørn Hove
Existing methods for complexity estimation are typically developed for entire documents. This limitation in scope makes them inapplicable for shorter pieces of text, such as health…
Text-To-KG Alignment: Comparing Current Methods on Classification Tasks
Sondre Wold, Lilja Øvrelid, Erik Velldal
In contrast to large text corpora, knowledge graphs (KG) provide dense and structured representations of factual information. This makes them attractive for systems that supplement…
NorQuAD: Norwegian Question Answering Dataset
Sardana Ivanova, Fredrik Aas Andreassen, Matias Jentoft +2
In this paper we present NorQuAD: the first Norwegian question answering dataset for machine reading comprehension. The dataset consists of 4,752 manually created question-answer p…