9 citations · 21 across the 8 of their papers we have counts for
7 papers · 1 filter
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…
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…
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…