Papers by Kobi Gal

2 papers
Detecting Suicide Risk in Online Counseling Services: A Study in a Low-Resource Language (2022.coling-1)

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Challenge: Existing domain-specific models for detecting suicide are lacking in low-resource languages.
Approach: They propose a model that combines pre-trained language models with a fixed set of suicidal cues and a two-stage fine-tuning process to detect SI.
Outcome: The proposed model outperforms baseline models even early on in the conversation and performs well across genders and age groups.
Combining Psychological Theory with Language Models for Suicide Risk Detection (2023.findings-eacl)

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Challenge: Existing models for suicide prevention are limited in domains and are not available in low-resource languages.
Approach: They propose a computational model that combines pre-trained language models with a fixed set of manually crafted suicidal cues and a two-stage fine-tuning process to detect suicide risk.
Outcome: The proposed model outperforms baseline models even early on in the conversation and performs well across genders and age groups.

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