Search Results for author:
Found 7 papers, 1 papers with code
On Detecting Cherry-picking in News Coverage Using Large Language Models
This study introduces Cherry, an innovative approach for automatically detecting cherry-picked statements in news articles by finding missing important statements in the target news story.
A Dashboard for Mitigating the COVID-19 Misinfodemic
This paper describes the current milestones achieved in our ongoing project that aims to understand the surveillance of, impact of and intervention on COVID-19 misinfodemic on Twitter.
Proppy: A System to Unmask Propaganda in Online News
We present proppy, the first publicly available real-world, real-time propaganda detection system for online news, which aims at raising awareness, thus potentially limiting the impact of propaganda and helping fight disinformation.
Tanbih: Get To Know What You Are Reading
We introduce Tanbih, a news aggregator with intelligent analysis tools to help readers understanding what's behind a news story.
ClaimRank: Detecting Check-Worthy Claims in Arabic and English
We present ClaimRank, an online system for detecting check-worthy claims.
Cross-language Learning with Adversarial Neural Networks
We address the problem of cross-language adaptation for question-question similarity reranking in community question answering, with the objective to port a system trained on one input language to another input language given labeled training data for the first language and only unlabeled data for the second language.
Cross-language Learning with Adversarial Neural Networks: Application to Community Question Answering
We address the problem of cross-language adaptation for question-question similarity reranking in community question answering, with the objective to port a system trained on one input language to another input language given labeled training data for the first language and only unlabeled data for the second language.
