Abstract

History repeats itself, sometimes in a bad way. Preventing natural or man-made disasters requires being aware of these patterns and taking pre-emptive action to address and reduce them, or ideally, eliminate them. Emerging events, such as the COVID pandemic and the Ukraine Crisis, require a time-sensitive comprehensive understanding of the situation to allow for appropriate decision-making and effective action response. Automated generation of situation reports can significantly reduce the time, effort, and cost for domain experts when preparing their official human-curated reports. However, AI research toward this goal has been very limited, and no successful trials have yet been conducted to automate such report generation and “what-if” disaster forecasting. Pre-existing natural language processing and information retrieval techniques are insufficient to identify, locate, and summarize important information, and lack detailed, structured, and strategic awareness. In this talk I will present SmartBook, a novel framework that cannot be solved by large language models alone, to consume large volumes of multimodal multilingual news data and produce a structured situation report with multiple hypotheses (claims) summarized and grounded with rich links to factual evidence through multimodal knowledge extraction, claim detection, fact checking, misinformation detection and factual error correction. Furthermore, SmartBook can also serve as a novel news event simulator, or an intelligent prophetess.  Given “What-if” conditions and dimensions elicited from a domain expert user concerning a disaster scenario, SmartBook will induce schemas from historical events, and automatically generate a complex event graph along with a timeline of news articles that describe new simulated events and character-centric stories based on a new Λ-shaped attention mask that can generate text with infinite length. By effectively simulating disaster scenarios in both event graph and natural language format, we expect SmartBook will greatly assist humanitarian workers and policymakers to exercise reality checks, and thus better prevent and respond to future disasters.

Bio

Heng Ji is a professor at Computer Science Department, and an affiliated faculty member at Electrical and Computer Engineering Department and Coordinated Science Laboratory of University of Illinois Urbana-Champaign. She is an Amazon Scholar. She is the Founding Director of Amazon-Illinois Center on AI for Interactive Conversational Experiences (AICE). She received her B.A. and M. A. in Computational Linguistics from Tsinghua University, and her M.S. and Ph.D. in Computer Science from New York University. Her research interests focus on Natural Language Processing, especially on Multimedia Multilingual Information Extraction, Knowledge-enhanced Large Language Models, Knowledge-driven Generation and Conversational AI. She was selected as a Young Scientist to attend the 6th World Laureates Association Forum, and selected to participate in DARPA AI Forward in 2023. She was selected as “Young Scientist” and a member of the Global Future Council on the Future of Computing by the World Economic Forum in 2016 and 2017. The awards she received include Women Leaders of Conversational AI (Class of 2023) by Project Voice, “AI’s 10 to Watch” Award by IEEE Intelligent Systems in 2013, NSF CAREER award in 2009, PACLIC2012 Best paper runner-up, “Best of ICDM2013” paper award, “Best of SDM2013” paper award, ACL2018 Best Demo paper nomination, ACL2020 Best Demo Paper Award, NAACL2021 Best Demo Paper Award, Google Research Award in 2009 and 2014, IBM Watson Faculty Award in 2012 and 2014 and Bosch Research Award in 2014-2018. She was invited to testify to the U.S. House Cybersecurity, Data Analytics, & IT Committee as an AI expert in 2023. She was invited by the Secretary of the U.S. Air Force and AFRL to join Air Force Data Analytics Expert Panel to inform the Air Force Strategy 2030, and invited to speak at the Federal Information Integrity R&D Interagency Working Group (IIRD IWG) briefing in 2023. She is the lead of many multi-institution projects and tasks, including the U.S. ARL projects on information fusion and knowledge networks construction, DARPA ECOLE MIRACLE team, DARPA KAIROS RESIN team and DARPA DEFT Tinker Bell team. She has coordinated the NIST TAC Knowledge Base Population task 2010-2022. She was the associate editor for IEEE/ACM Transaction on Audio, Speech, and Language Processing, and served as the Program Committee Co-Chair of many conferences including NAACL-HLT2018 and AACL-IJCNLP2022. She is elected as the North American Chapter of the Association for Computational Linguistics (NAACL) secretary 2020-2023. Her research has been widely supported by the U.S. government agencies (DARPA, NSF, DoE, ARL, IARPA, AFRL, DHS) and industry (Apple, Amazon, Google, Facebook, Bosch, IBM, Disney).