no code implementations • Findings (NAACL) 2022 • Luis Guzman-Nateras, Viet Lai, Amir Pouran Ben Veyseh, Franck Dernoncourt, Thien Nguyen
In particular, we introduce SuicideED: a new dataset for the ED task that features seven suicidal event types to comprehensively capture suicide actions and ideation, and general risk and protective factors.
no code implementations • NAACL 2022 • Luis Guzman-Nateras, Minh Van Nguyen, Thien Nguyen
In this work, we focus on Cross-Lingual Event Detection where a model is trained on data from a \textit{source} language but its performance is evaluated on data from a second, \textit{target}, language.
no code implementations • ICLR 2020 • Isaac Ahern, Adam Noack, Luis Guzman-Nateras, Dejing Dou, Boyang Li, Jun Huan
The problem of explaining deep learning models, and model predictions generally, has attracted intensive interest recently.