CARE fine-tunes LLMs on counselor-validated crisis dialogues to produce responses with stronger semantic and strategic alignment to expert standards than general-purpose models in Hebrew and Arabic.
Title resolution pending
2 Pith papers cite this work, alongside 619 external citations. Polarity classification is still indexing.
2
Pith papers citing it
619
external citations · external index
citation-role summary
background 1
citation-polarity summary
fields
cs.CL 2years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
support 1representative citing papers
MARBERT is fine-tuned on 24,513 Arabic tweets for sentiment analysis, with the claim that the resulting scheme shows promising accuracy versus prior techniques.
citing papers explorer
-
CARE: Counselor-Aligned Response Engine for Online Mental-Health Support
CARE fine-tunes LLMs on counselor-validated crisis dialogues to produce responses with stronger semantic and strategic alignment to expert standards than general-purpose models in Hebrew and Arabic.
-
Spam and Sentiment Detection in Arabic Tweets Using MARBERT Model
MARBERT is fine-tuned on 24,513 Arabic tweets for sentiment analysis, with the claim that the resulting scheme shows promising accuracy versus prior techniques.