Automated Depression Assessment Using RLHF And RLAIF Instructions In Machine Learning

4 Jul
Posted on Author

Authors: Ratnesh Kumar Sharma, Prof. (Dr.) Satya Singh

Abstract: In the domain of machine learning, a useful application of Reinforcement Learning from Human Feedback (RLHF) and Reinforcement Learning from AI Feedback (RLAIF) lies in the automated evaluation of depression in patients of all age groups. By leveraging natural language processing (NLP) techniques and machine learning algorithms, this paper aims to develop effective models for detecting depression through language patterns and assessing the severity of depression. The study demonstrates that RLHF significantly enhances model performance through the incorporation of expert feedback, while RLAIF offers a scalable solution that utilizes AI-driven insights. The findings suggest that both methodologies hold promise for improving automated mental health assessment tools, ultimately contributing to more effective diagnoses and follow up counselling/ treatment.

DOI: https://doi.org/10.5281/zenodo.15804092