UrduFake@FIRE2021: Shared Track on Fake News Identification in Urdu
원문 초록
This study reports the second shared task named as UrduFake@FIRE2021 on identifying fake news detection in Urdu language. This is a binary classification problem in which the task is to classify a given news article into two classes: (i) real news, or (ii) fake news. In this shared task, 34 teams from 7 different countries (China, Egypt, Israel, India, Mexico, Pakistan, and UAE) registered to participate in the shared task, 18 teams submitted their experimental results and 11 teams submitted their technical reports. The proposed systems were based on various count-based features and used different classifiers as well as neural network architectures. The stochastic gradient descent (SGD) algorithm outperformed other classifiers and achieved 0.679 F-score.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
A Decision-Based Heterogenous Graph Attention Network for Multi-Class Fake News Detection
UNITE-FND: Reframing Multimodal Fake News Detection through Unimodal Scene Translation
DCR: Quantifying Data Contamination in LLMs Evaluation
Inverse Scene Text Removal
EDINET-Bench: Evaluating LLMs on Complex Financial Tasks using Japanese Financial Statements
Synergizing LLMs with Global Label Propagation for Multimodal Fake News Detection
토론
이 논문과 연결된 포럼 글이 아직 없습니다.