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pro vyhledávání: '"Truskovskyi, Kyryl"'
Autor:
Hagag, Ben, Harpaz, Liav, Semo, Gil, Bernsohn, Dor, Saha, Rohit, Vaezipoor, Pashootan, Truskovskyi, Kyryl, Spanakis, Gerasimos
This paper presents the results of the LegalLens Shared Task, focusing on detecting legal violations within text in the wild across two sub-tasks: LegalLens-NER for identifying legal violation entities and LegalLens-NLI for associating these violatio
Externí odkaz:
http://arxiv.org/abs/2410.12064
Autor:
Bernsohn, Dor, Semo, Gil, Vazana, Yaron, Hayat, Gila, Hagag, Ben, Niklaus, Joel, Saha, Rohit, Truskovskyi, Kyryl
In this study, we focus on two main tasks, the first for detecting legal violations within unstructured textual data, and the second for associating these violations with potentially affected individuals. We constructed two datasets using Large Langu
Externí odkaz:
http://arxiv.org/abs/2402.04335
Autor:
Saha, Rohit, Fang, Mengyi, Yasodhara, Angeline, Truskovskyi, Kyryl, Asgarian, Azin, Homola, Daniel, Shah, Raahil, Dieleman, Frederik, Weatheritt, Jack, Rogers, Thomas
After a natural disaster, such as a hurricane, millions are left in need of emergency assistance. To allocate resources optimally, human planners need to accurately analyze data that can flow in large volumes from several sources. This motivates the
Externí odkaz:
http://arxiv.org/abs/2206.09242
Publikováno v:
In Chaos, Solitons and Fractals: the interdisciplinary journal of Nonlinear Science, and Nonequilibrium and Complex Phenomena April 2017 97:44-50
Akademický článek
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