3 citations · 5 across the 5 of their papers we have counts for
8 papers
Nearest Neighbor Language Models for Stylistic Controllable Generation
Severino Trotta, Lucie Flek, Charles Welch
Recent language modeling performance has been greatly improved by the use of external memory. This memory encodes the context so that similar contexts can be recalled during decodi…
Mitigating Toxic Degeneration with Empathetic Data: Exploring the Relationship Between Toxicity and Empathy
Allison Lahnala, Charles Welch, Béla Neuendorf +1
Large pre-trained neural language models have supported the effectiveness of many NLP tasks, yet are still prone to generating toxic language hindering the safety of their use. Usi…
Modeling Proficiency with Implicit User Representations
Kim Breitwieser, Allison Lahnala, Charles Welch +2
We introduce the problem of proficiency modeling: Given a user's posts on a social media platform, the task is to identify the subset of posts or topics for which the user has some…
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…