Learning to Read for Automated Fact Checking

•••► Topic: Learning to Read for Automated Fact Checking •••► Speaker: Isabelle Augenstein, Assistant Professor, University of Copenhagen •••► Who will be interested: The topic of the talk will be relevant to people working in machine learning, natural language processing, information retrieval, knowledge base engineering, or political science. To understand the topic, basic knowledge of machine learning and NLP is required. •••► Where: Coworking "Chasopys" •••► When: Wednesday, November 22th, 7 PM •••► Language: English •••► Tickets and Registration: https://gram.ly/GLBj "The spread of misinformation and disinformation is growing, and it’s having a big impact on interpersonal communications, politics and even science. Traditional methods, e.g., manual fact-checking by reporters, cannot keep up with the growth of information. On the other hand, there has been much progress in natural language processing recently, partly due to the resurgence of neural methods. How can natural language processing methods fill this gap and help to automatically check facts? This talk will explore different ways to frame fact checking and detail our ongoing work on learning to encode documents for automated fact checking, as well as describe future challenges."