2 citations · 2 across the 2 of their papers we have counts for
3 papers · 1 filter
Semeval-2022 Task 1: CODWOE -- Comparing Dictionaries and Word Embeddings
Timothee Mickus, Kees van Deemter, Mathieu Constant +1
Word embeddings have advanced the state of the art in NLP across numerous tasks. Understanding the contents of dense neural representations is of utmost interest to the computation…
A Game Interface to Study Semantic Grounding in Text-Based Models
Timothee Mickus, Mathieu Constant, Denis Paperno
Can language models learn grounded representations from text distribution alone? This question is both central and recurrent in natural language processing; authors generally agree…
What do you mean, BERT? Assessing BERT as a Distributional Semantics Model
Timothee Mickus, Denis Paperno, Mathieu Constant +1
Contextualized word embeddings, i.e. vector representations for words in context, are naturally seen as an extension of previous noncontextual distributional semantic models. In th…