CARE: Counselor-Aligned Response Engine for Online Mental-Health Support
Mental health challenges are increasing worldwide, straining emotional support services and leading to counselor overload. This can result in delayed responses during critical situations, such as suicidal ideation, where timely intervention is essential. While large language models (LLMs) have shown strong generative capabilities, their application in low-resource languages, especially in sensitive domains like mental health, remains underexplored. Furthermore, existing LLM-based agents often struggle to replicate the supportive language and intervention strategies used by professionals due to a lack of training on large-scale, real-world datasets. To address this, we propose CARE (Counse...
| Authors | Hagai Astrin, Ayal Swaid, Avi Segal et al. |
|---|---|
| Primary category | cs.CL |
| Published | 23 April 2026 |
| Last updated at source | 6 May 2026 |
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