1 code implementation • 11 Jan 2024 • Israa Jaradat, Haiqi Zhang, Chengkai Li
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.
no code implementations • EACL 2021 • Zhengyuan Zhu, Kevin Meng, Josue Caraballo, Israa Jaradat, Xiao Shi, Zeyu Zhang, Farahnaz Akrami, Haojin Liao, Fatma Arslan, Damian Jimenez, Mohanmmed Samiul Saeef, Paras Pathak, Chengkai Li
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.
no code implementations • ACL 2020 • Yunyao Li, Gr, Tyrone ison, Patricia Silveyra, Ali Douraghy, Xinyu Guan, Thomas Kieselbach, Chengkai Li, Haiqi Zhang
Just as SARS-CoV-2, a new form of coronavirus continues to infect a growing number of people around the world, harmful misinformation about the outbreak also continues to spread.
no code implementations • LREC 2020 • Fatma Arslan, Josue Caraballo, Damian Jimenez, Chengkai Li
In this paper, we introduce an extension of the Berkeley FrameNet for the structured and semantic modeling of factual claims.
no code implementations • 29 Apr 2020 • Fatma Arslan, Naeemul Hassan, Chengkai Li, Mark Tremayne
In this paper we present the ClaimBuster dataset of 23, 533 statements extracted from all U. S. general election presidential debates and annotated by human coders.
1 code implementation • 18 Mar 2020 • Farahnaz Akrami, Mohammed Samiul Saeef, Qingheng Zhang, Wei Hu, Chengkai Li
A more fundamental defect of these models is that the link prediction scenario, given such data, is non-existent in the real-world.
1 code implementation • 10 Mar 2020 • Zequn Sun, Qingheng Zhang, Wei Hu, Chengming Wang, Muhao Chen, Farahnaz Akrami, Chengkai Li
Recent advancement in KG embedding impels the advent of embedding-based entity alignment, which encodes entities in a continuous embedding space and measures entity similarities based on the learned embeddings.
1 code implementation • 24 Feb 2020 • Shuxin Li, Gong Cheng, Chengkai Li
We prove that verifying the success of a sub-query turns into finding an entity (called a certificate) that satisfies a distance-based condition about the query entities.
1 code implementation • 18 Feb 2020 • Kevin Meng, Damian Jimenez, Fatma Arslan, Jacob Daniel Devasier, Daniel Obembe, Chengkai Li
We present a study on the efficacy of adversarial training on transformer neural network models, with respect to the task of detecting check-worthy claims.
no code implementations • ACL 2019 • Sarthak Majithia, Fatma Arslan, Sumeet Lubal, Damian Jimenez, Priyank Arora, Josue Caraballo, Chengkai Li
We present ClaimPortal, a web-based platform for monitoring, searching, checking, and analyzing English factual claims on Twitter from the American political domain.
1 code implementation • 16 Aug 2017 • Zequn Sun, Wei Hu, Chengkai Li
Our experimental results on real-world datasets show that this approach significantly outperforms the state-of-the-art embedding approaches for cross-lingual entity alignment and could be complemented with methods based on machine translation.
no code implementations • 15 Sep 2014 • Abolfazl Asudeh, Gensheng Zhang, Naeemul Hassan, Chengkai Li, Gergely V. Zaruba
This design is both sufficient and efficient, as it is proven to find a short terminal question sequence.