Summary of Fine Tuning Large Language Models to Deliver Cbt For Depression, by Talha Tahir
Fine Tuning Large Language Models to Deliver CBT for Depression
by Talha Tahir
First submitted to arxiv on: 29 Nov 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Human-Computer Interaction (cs.HC)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper explores the feasibility of using fine-tuned large language models (LLMs) to deliver Cognitive Behavioral Therapy (CBT) for depression. The researchers used synthetic CBT transcripts to fine-tune three LLMs: Mistral 7b v0.3, Qwen 2.5 7b, and Llama 3.1 8b. They evaluated the models’ performance using a modified Cognitive Therapy Rating Scale (CTRS) and found that the CBT-tuned models significantly outperformed their instruct-tuned counterparts. The study demonstrates that fine-tuning LLMs with CBT-specific data can encode therapeutic competencies, but technical and ethical considerations must be addressed before clinical deployment. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at using special kinds of artificial intelligence called large language models (LLMs) to help people with depression. They used fake conversations to train three types of LLMs: Mistral 7b v0.3, Qwen 2.5 7b, and Llama 3.1 8b. The researchers tested the models by giving them tasks that a therapist would do, like helping someone with depression. They found that the models got better at doing these tasks when they were trained on CBT (cognitive behavioral therapy) ideas. This is important because it might be possible to use computers to help people get the therapy they need. |
Keywords
» Artificial intelligence » Fine tuning » Llama
