Summary of Psychological Assessments with Large Language Models: a Privacy-focused and Cost-effective Approach, by Sergi Blanco-cuaresma
Psychological Assessments with Large Language Models: A Privacy-Focused and Cost-Effective Approach
by Sergi Blanco-Cuaresma
First submitted to arxiv on: 5 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Computers and Society (cs.CY)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This research explores the application of Large Language Models (LLMs) to analyze Reddit user comments for identifying critical excerpts that support suicidal risk assessments. The study focuses on using open-source LLMs with low computational requirements, ensuring data privacy and accessibility. A carefully crafted prompt guides the model’s text completion, achieving outstanding results according to evaluation metrics. This work is part of the Computational Linguistics and Clinical Psychology (CLPsych) 2024 shared task. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study uses computer models to read and understand text comments from Reddit users. It wants to find important parts that show someone might be at risk of suicide, and then summarize it all to agree with what was expected. The research only uses free-to-use language models that can run on regular computers, so data stays private and anyone can do it. Even though the method is simple, it works really well according to some tests. |
Keywords
» Artificial intelligence » Prompt
