Science, or slop? · Science Slop Index

· Science Slop Index

2 min read Original article ↗

A paper can read well sentence by sentence while its science does not connect. Unlike token-level AI detectors, the Science Slop Index reads the scientific reasoning: whether sections build on one another, claims and citations are argued, and the method and evidence can be inspected.

Paste a link or upload a PDF / LaTeX .zip. Your report is private: you get a key, and you decide on the report whether to list it.

SciSlop v2 is being written with the community. Flag slop on any paper and become a . How ↓

Click the center paper to open its full report; click a side one to bring it forward. Highlights on each first page are the findings.

Open call · SciSlop v2

Become a co-author of SciSlop v2.

The next version is built from what the community finds. Mark slop the index missed, dispute what it got wrong, name patterns it does not know yet.
Every contribution is credited. Substantial ones earn co-authorship on the v2 paper.

Contributors

Everyone who flagged slop or named a pattern. Substantial contributors are invited as co-authors of SciSlop v2.

News

  • Oct 2026Paper, benchmark, code, and this site are out. Science or Slop? is on arXiv (2610.00531), SciSlopBench on Hugging Face, the code on GitHub.
  • ComingA Science Slop Index for every ICLR submission. We are preparing to run the six measures over this year's ~60K ICLR submissions and publish the venue-wide picture: how much scientific slop is in the pool, which patterns, and how it relates to the outcomes.
  • Looking forAPI credit sponsorship. The four rule-based measures run on our own machines; the two model-based ones (Argument graph, Figure exposition) need roughly a million model calls for 60K papers. If your organization can sponsor API credits, write to yerim.oh@vision.snu.ac.kr. Sponsors are acknowledged in the release.

Team

The people behind Science or Slop? and this site.

Cite

If you use the Science Slop Index, SciSlopBench, or the code, please cite the paper.

@article{oh2026scislop,
  title         = {Science or Slop?: Benchmarking and Mitigating Scientific Slop in AI-Generated Papers},
  author        = {Oh, Yerim and Lee, Young-Jun and Ahn, Jaewoo and Kim, Gunhee and Kang, Dongyeop},
  journal       = {arXiv preprint arXiv:2610.00531},
  year          = {2026},
  eprint        = {2610.00531},
  archivePrefix = {arXiv},
  url           = {https://arxiv.org/abs/2610.00531}
}