Summary of Is Open-source There Yet? a Comparative Study on Commercial and Open-source Llms in Their Ability to Label Chest X-ray Reports, by Felix J. Dorfner et al.
Is Open-Source There Yet? A Comparative Study on Commercial and Open-Source LLMs in Their Ability to Label Chest X-Ray Reports
by Felix J. Dorfner, Liv Jürgensen, Leonhard Donle, Fares Al Mohamad, Tobias R. Bodenmann, Mason C. Cleveland, Felix Busch, Lisa C. Adams, James Sato, Thomas Schultz, Albert E. Kim, Jameson Merkow, Keno K. Bressem, Christopher P. Bridge
First submitted to arxiv on: 19 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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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 As the field of large language models (LLMs) continues to evolve, researchers have been exploring various applications for these powerful tools. This paper focuses on comparing GPT-4, a state-of-the-art model designed for extracting information from radiology reports, with other leading open-source LLMs. The authors aim to provide a real-world comparison of GPT-4’s performance in this specific task, shedding light on its strengths and weaknesses compared to established models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study compares the language processing capabilities of different large language models, including GPT-4. Scientists are using these powerful tools to analyze medical reports and extract important information. The researchers want to see how well GPT-4 works at this job compared to other similar models. They’re trying to figure out what makes it good or not so good. |
Keywords
» Artificial intelligence » Gpt
