9 citations · 21 across the 8 of their papers we have counts for
10 papers
When Claims Evolve: Evaluating and Enhancing the Robustness of Embedding Models Against Misinformation Edits
Jabez Magomere, Emanuele La Malfa, Manuel Tonneau +2
Online misinformation remains a critical challenge, and fact-checkers increasingly rely on claim matching systems that use sentence embedding models to retrieve relevant fact-check…
SynDy: Synthetic Dynamic Dataset Generation Framework for Misinformation Tasks
Michael Shliselberg, Ashkan Kazemi, Scott A. Hale +1
Diaspora communities are disproportionately impacted by off-the-radar misinformation and often neglected by mainstream fact-checking efforts, creating a critical need to scale-up e…
Misinformation as Information Pollution
Ashkan Kazemi, Rada Mihalcea
Social media feed algorithms are designed to optimize online social engagements for the purpose of maximizing advertising profits, and therefore have an incentive to promote contro…
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…
Tiplines to Combat Misinformation on Encrypted Platforms: A Case Study of the 2019 Indian Election on WhatsApp
Ashkan Kazemi, Kiran Garimella, Gautam Kishore Shahi +2
There is currently no easy way to fact-check content on WhatsApp and other end-to-end encrypted platforms at scale. In this paper, we analyze the usefulness of a crowd-sourced "tip…
Claim Matching Beyond English to Scale Global Fact-Checking
Ashkan Kazemi, Kiran Garimella, Devin Gaffney +1
Manual fact-checking does not scale well to serve the needs of the internet. This issue is further compounded in non-English contexts. In this paper, we discuss claim matching as a…
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…
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…