TY - GEN
T1 - Overview of the CLPsych 2024 Shared Task
T2 - 9th Workshop on Computational Linguistics and Clinical Psychology, CLPsych 2024
AU - Chim, Jenny
AU - Tsakalidis, Adam
AU - Gkoumas, Dimitris
AU - Atzil-Slonim, Dana
AU - Ophir, Yaakov
AU - Zirikly, Ayah
AU - Resnik, Philip
AU - Liakata, Maria
N1 - Publisher Copyright:
©2024 Association for Computational Linguistics.
PY - 2024
Y1 - 2024
N2 - We present the overview of the CLPsych 2024 Shared Task, focusing on leveraging open source Large Language Models (LLMs) for identifying textual evidence that supports the suicidal risk level of individuals on Reddit. In particular, given a Reddit user, their predetermined suicide risk level (‘Low’, ‘Moderate’ or ‘High’) and all of their posts in the r/SuicideWatch subreddit, we frame the task of identifying relevant pieces of text in their posts supporting their suicidal classification in two ways: (a) on the basis of evidence highlighting (extracting sub-phrases of the posts) and (b) on the basis of generating a summary of such evidence. We annotate a sample of 125 users and introduce evaluation metrics based on (a) BERTScore and (b) natural language inference for the two sub-tasks, respectively. Finally, we provide an overview of the system submissions and summarise the key findings.
AB - We present the overview of the CLPsych 2024 Shared Task, focusing on leveraging open source Large Language Models (LLMs) for identifying textual evidence that supports the suicidal risk level of individuals on Reddit. In particular, given a Reddit user, their predetermined suicide risk level (‘Low’, ‘Moderate’ or ‘High’) and all of their posts in the r/SuicideWatch subreddit, we frame the task of identifying relevant pieces of text in their posts supporting their suicidal classification in two ways: (a) on the basis of evidence highlighting (extracting sub-phrases of the posts) and (b) on the basis of generating a summary of such evidence. We annotate a sample of 125 users and introduce evaluation metrics based on (a) BERTScore and (b) natural language inference for the two sub-tasks, respectively. Finally, we provide an overview of the system submissions and summarise the key findings.
UR - http://www.scopus.com/inward/record.url?scp=85185569942&partnerID=8YFLogxK
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AN - SCOPUS:85185569942
T3 - CLPsych 2024 - 9th Workshop on Computational Linguistics and Clinical Psychology, Proceedings of the Workshop
SP - 177
EP - 190
BT - CLPsych 2024 - 9th Workshop on Computational Linguistics and Clinical Psychology, Proceedings of the Workshop
A2 - Yates, Andrew
A2 - Desmet, Bart
A2 - Prud�hommeaux, Emily
A2 - Zirikly, Ayah
A2 - Bedrick, Steven
A2 - MacAvaney, Sean
A2 - Bar, Kfir
A2 - Ireland, Molly
A2 - Ophir, Yaakov
A2 - Ophir, Yaakov
PB - Association for Computational Linguistics (ACL)
Y2 - 21 March 2024
ER -