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pro vyhledávání: '"George, Enfa"'
This paper presents a question-answering approach to extract document-level event-argument structures. We automatically ask and answer questions for each argument type an event may have. Questions are generated using manually defined templates and ge
Externí odkaz:
http://arxiv.org/abs/2404.16413
This paper presents multiple question generation strategies for document-level event argument extraction. These strategies do not require human involvement and result in uncontextualized questions as well as contextualized questions grounded on the e
Externí odkaz:
http://arxiv.org/abs/2404.04770
Autor:
George, Enfa, Surdeanu, Mihai
We introduce SexTok, a multi-modal dataset composed of TikTok videos labeled as sexually suggestive (from the annotator's point of view), sex-educational content, or neither. Such a dataset is necessary to address the challenge of distinguishing betw
Externí odkaz:
http://arxiv.org/abs/2307.03274
Autor:
Xie, Zhengnan, Kwak, Alice Saebom, George, Enfa, Dozal, Laura W., Van, Hoang, Jah, Moriba, Furfaro, Roberto, Jansen, Peter
Space situational awareness typically makes use of physical measurements from radar, telescopes, and other assets to monitor satellites and other spacecraft for operational, navigational, and defense purposes. In this work we explore using textual in
Externí odkaz:
http://arxiv.org/abs/2201.05721