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| Main Authors: | , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.20252 |
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| _version_ | 1866909331701628928 |
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| author | Fouesneau, Morgan Momcheva, Ivelina G. Chadayammuri, Urmila Demianenko, Mariia Dumont, Antoine Hviding, Raphael E. Kahle, K. Angelique Pulatova, Nadiia Rajpoot, Bhavesh Scheuck, Marten B. Seeburger, Rhys Semenov, Dmitry Villaseñor, Jaime I. |
| author_facet | Fouesneau, Morgan Momcheva, Ivelina G. Chadayammuri, Urmila Demianenko, Mariia Dumont, Antoine Hviding, Raphael E. Kahle, K. Angelique Pulatova, Nadiia Rajpoot, Bhavesh Scheuck, Marten B. Seeburger, Rhys Semenov, Dmitry Villaseñor, Jaime I. |
| contents | ChatGPT and other state-of-the-art large language models (LLMs) are rapidly transforming multiple fields, offering powerful tools for a wide range of applications. These models, commonly trained on vast datasets, exhibit human-like text generation capabilities, making them useful for research tasks such as ideation, literature review, coding, drafting, and outreach. We conducted a study involving 13 astronomers at different career stages and research fields to explore LLM applications across diverse tasks over several months and to evaluate their performance in research-related activities. This work was accompanied by an anonymous survey assessing participants' experiences and attitudes towards LLMs. We provide a detailed analysis of the tasks attempted and the survey answers, along with specific output examples. Our findings highlight both the potential and limitations of LLMs in supporting research while also addressing general and research-specific ethical considerations. We conclude with a series of recommendations, emphasizing the need for researchers to complement LLMs with critical thinking and domain expertise, ensuring these tools serve as aids rather than substitutes for rigorous scientific inquiry. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_20252 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | What is the Role of Large Language Models in the Evolution of Astronomy Research? Fouesneau, Morgan Momcheva, Ivelina G. Chadayammuri, Urmila Demianenko, Mariia Dumont, Antoine Hviding, Raphael E. Kahle, K. Angelique Pulatova, Nadiia Rajpoot, Bhavesh Scheuck, Marten B. Seeburger, Rhys Semenov, Dmitry Villaseñor, Jaime I. Instrumentation and Methods for Astrophysics Artificial Intelligence ChatGPT and other state-of-the-art large language models (LLMs) are rapidly transforming multiple fields, offering powerful tools for a wide range of applications. These models, commonly trained on vast datasets, exhibit human-like text generation capabilities, making them useful for research tasks such as ideation, literature review, coding, drafting, and outreach. We conducted a study involving 13 astronomers at different career stages and research fields to explore LLM applications across diverse tasks over several months and to evaluate their performance in research-related activities. This work was accompanied by an anonymous survey assessing participants' experiences and attitudes towards LLMs. We provide a detailed analysis of the tasks attempted and the survey answers, along with specific output examples. Our findings highlight both the potential and limitations of LLMs in supporting research while also addressing general and research-specific ethical considerations. We conclude with a series of recommendations, emphasizing the need for researchers to complement LLMs with critical thinking and domain expertise, ensuring these tools serve as aids rather than substitutes for rigorous scientific inquiry. |
| title | What is the Role of Large Language Models in the Evolution of Astronomy Research? |
| topic | Instrumentation and Methods for Astrophysics Artificial Intelligence |
| url | https://arxiv.org/abs/2409.20252 |