379 citations · 431 across the 8 of their papers we have counts for
13 papers
Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Models
Oana Ignat, Zhijing Jin, Artem Abzaliev +19
Recent progress in large language models (LLMs) has enabled the deployment of many generative NLP applications. At the same time, it has also led to a misleading public discourse t…
Query Rewriting for Effective Misinformation Discovery
Ashkan Kazemi, Artem Abzaliev, Naihao Deng +4
We propose a novel system to help fact-checkers formulate search queries for known misinformation claims and effectively search across multiple social media platforms. We introduce…
Matching Tweets With Applicable Fact-Checks Across Languages
Ashkan Kazemi, Zehua Li, Verónica Pérez-Rosas +2
An important challenge for news fact-checking is the effective dissemination of existing fact-checks. This in turn brings the need for reliable methods to detect previously fact-ch…
Exploring Self-Identified Counseling Expertise in Online Support Forums
Allison Lahnala, Yuntian Zhao, Charles Welch +5
A growing number of people engage in online health forums, making it important to understand the quality of the advice they receive. In this paper, we explore the role of expertise…
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…
Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper)
Santiago Castro, Devamanyu Hazarika, Verónica Pérez-Rosas +3
Sarcasm is often expressed through several verbal and non-verbal cues, e.g., a change of tone, overemphasis in a word, a drawn-out syllable, or a straight looking face. Most of the…
Look Who's Talking: Inferring Speaker Attributes from Personal Longitudinal Dialog
Charles Welch, Verónica Pérez-Rosas, Jonathan K. Kummerfeld +1
We examine a large dialog corpus obtained from the conversation history of a single individual with 104 conversation partners. The corpus consists of half a million instant message…
Automatic Detection of Fake News
Verónica Pérez-Rosas, Bennett Kleinberg, Alexandra Lefevre +1
The proliferation of misleading information in everyday access media outlets such as social media feeds, news blogs, and online newspapers have made it challenging to identify trus…