Papers by Luis Guzman-Nateras
Cross-Lingual Event Detection via Optimized Adversarial Training (2022.naacl-main)
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| Challenge: | Recent work in this area has harnessed the language-invariant qualities of pre-trained Multi-lingual Language Models. |
| Approach: | They propose to use adversarial language adaptation to train a model to detect events in a target language. |
| Outcome: | The proposed model achieves state-of-the-art on 8 different language pairs, using 4 languages from unrelated families. |
Event Detection for Suicide Understanding (2022.findings-naacl)
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| Challenge: | Existing methods for detecting suicide-related events are limited . recognizing suicide- related events is critical to understanding the condition, authors argue . |
| Approach: | They propose a dataset to detect event trigger words of suicide-related events in forums . they propose 'suicideED' dataset to capture suicidal actions and ideation . |
| Outcome: | The proposed dataset captures suicide actions and ideation, and general risk and protective factors. |