Zero-shot Explainable Mental Health Analysis on Social Media by incorporating Mental Scales

arXiv:2402.10948v1 Announce Type: new
Abstract: Traditional discriminative approaches in mental health analysis are known for their strong capacity but lack interpretability and demand large-scale annotated data. On the other hand, generative approaches, such as those based on large language models (LLMs),have the potential to get rid of heavy annotations and provide explanations. However, their capabilities still fall short compared to discriminative approaches, and their explanations may be unreliable due to the fact that the generation of explanation is a black-box …

abstract analysis annotated data arxiv capacity cs.ai cs.cl data demand generative health interpretability language language models large language large language models llms media mental health scale social social media type zero-shot