230 citations · 680 across the 32 of their papers we have counts for
4 papers · 1 filter
Exploring the Value of Personalized Word Embeddings
Charles Welch, Jonathan K. Kummerfeld, Verónica Pérez-Rosas +1
In this paper, we introduce personalized word embeddings, and examine their value for language modeling. We compare the performance of our proposed prediction model when using pers…
Compositional Demographic Word Embeddings
Charles Welch, Jonathan K. Kummerfeld, Verónica Pérez-Rosas +1
Word embeddings are usually derived from corpora containing text from many individuals, thus leading to general purpose representations rather than individually personalized repres…
Improving Low Compute Language Modeling with In-Domain Embedding Initialisation
Charles Welch, Rada Mihalcea, Jonathan K. Kummerfeld
Many NLP applications, such as biomedical data and technical support, have 10-100 million tokens of in-domain data and limited computational resources for learning from it. How sho…
Analyzing the Surprising Variability in Word Embedding Stability Across Languages
Laura Burdick, Jonathan K. Kummerfeld, Rada Mihalcea
Word embeddings are powerful representations that form the foundation of many natural language processing architectures, both in English and in other languages. To gain further ins…