# Can AI Put Gamma-Ray Astrophysicists Out of a Job?

arXiv: https://arxiv.org/abs/2303.17853 · HTML: https://mlsanity.com/paper/2303.17853/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 14 references that are in the map.
- First posted on arXiv 31 Mar 2023.

## Builds on (most cited first, 1 of 1)

- [High-Resolution Image Synthesis with Latent Diffusion Models](https://mlsanity.com/paper/2112.10752/) (2021)

## Built on by (most cited first, 1 of 1)

- [AI, write an essay for me: A large-scale comparison of human-written versus ChatGPT-generated essays](https://mlsanity.com/paper/2304.14276/) (2023)

## Abstract (arXiv)

In what will likely be a litany of generative-model-themed arXiv submissions celebrating April the 1st, we evaluate the capacity of state-of-the-art transformer models to create a paper detailing the detection of a Pulsar Wind Nebula with a non-existent Imaging Atmospheric Cherenkov Telescope (IACT) Array. We do this to evaluate the ability of such models to interpret astronomical observations and sources based on language information alone, and to assess potential means by which fraudulently generated scientific papers could be identified during peer review (given that reliable generative model watermarking has yet to be deployed for these tools). We conclude that our jobs as astronomers are safe for the time being. From this point on, prompts given to ChatGPT and Stable Diffusion are shown in orange, text generated by ChatGPT is shown in black, whereas analysis by the (human) authors is in blue.