DepressLLM: Interpretable domain-adapted language model for depression detection from real-world narratives

Sehwan Moon, Aram Lee, Jeong Eun Kim +6

Advances in large language models (LLMs) have enabled a wide range of applications. However, depression prediction is hindered by the lack of large-scale, high-quality, and rigorou…