2 citations · 4 across the 4 of their papers we have counts for
6 papers
Multilingual and Multimodal Topic Modelling with Pretrained Embeddings
Elaine Zosa, Lidia Pivovarova
This paper presents M3L-Contrast -- a novel multimodal multilingual (M3L) neural topic model for comparable data that maps texts from multiple languages and images into a shared to…
Do Not Fire the Linguist: Grammatical Profiles Help Language Models Detect Semantic Change
Mario Giulianelli, Andrey Kutuzov, Lidia Pivovarova
Morphological and syntactic changes in word usage (as captured, e.g., by grammatical profiles) have been shown to be good predictors of a word's meaning change. In this work, we ex…
Grammatical Profiling for Semantic Change Detection
Mario Giulianelli, Andrey Kutuzov, Lidia Pivovarova
Semantics, morphology and syntax are strongly interdependent. However, the majority of computational methods for semantic change detection use distributional word representations w…
Three-part diachronic semantic change dataset for Russian
Andrey Kutuzov, Lidia Pivovarova
We present a manually annotated lexical semantic change dataset for Russian: RuShiftEval. Its novelty is ensured by a single set of target words annotated for their diachronic sema…
Topic modelling discourse dynamics in historical newspapers
Jani Marjanen, Elaine Zosa, Simon Hengchen +2
This paper addresses methodological issues in diachronic data analysis for historical research. We apply two families of topic models (LDA and DTM) on a relatively large set of his…
Capturing Evolution in Word Usage: Just Add More Clusters?
Matej Martinc, Syrielle Montariol, Elaine Zosa +1
The way the words are used evolves through time, mirroring cultural or technological evolution of society. Semantic change detection is the task of detecting and analysing word evo…