379 citations · 382 across the 2 of their papers we have counts for
9 papers
Extractive and Abstractive Explanations for Fact-Checking and Evaluation of News
Ashkan Kazemi, Zehua Li, Verónica Pérez-Rosas +1
In this paper, we explore the construction of natural language explanations for news claims, with the goal of assisting fact-checking and news evaluation applications. We experimen…
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…
Biased TextRank: Unsupervised Graph-Based Content Extraction
Ashkan Kazemi, Verónica Pérez-Rosas, Rada Mihalcea
We introduce Biased TextRank, a graph-based content extraction method inspired by the popular TextRank algorithm that ranks text spans according to their importance for language pr…
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…
Expressive Interviewing: A Conversational System for Coping with COVID-19
Charles Welch, Allison Lahnala, Verónica Pérez-Rosas +6
The ongoing COVID-19 pandemic has raised concerns for many regarding personal and public health implications, financial security and economic stability. Alongside many other unprec…
Towards Automatic Detection of Misinformation in Online Medical Videos
Rui Hou, Verónica Pérez-Rosas, Stacy Loeb +1
Recent years have witnessed a significant increase in the online sharing of medical information, with videos representing a large fraction of such online sources. Previous studies…