arXiv — cs.AI preprintsInternational2 October 2026
Science or Slop?: Benchmarking and Mitigating Scientific Slop in AI-Generated Papers
This is an official announcement record
Firsthand records what arXiv — cs.AI preprints announced and links to the original. The wording below is theirs, not ours.
arXiv:2610.00531v1 Announce Type: new Abstract: AI-generated content, often called AI slop, is increasingly common everywhere, particularly in academia. Slop in AI-generated scientific papers, however, has more complex patterns that cannot be easily detected by existing token-based AI detectors. Each part of such a paper looks plausible while the scientific reasoning that connects the parts breaks down, which can mislead how readers assess the work. We benchmark these failures as scientific slop through six measures across Structure, Argument, and Artifacts. We construct SciSlopBench with 390
Read the official announcement
Opens arxiv.org
More from arXiv — cs.AI preprints
- Heavy-Tailed Memory Traces in Long-Horizon Language Agents2 October 2026
- When Do Causal World Models Help Modular LLM Agents2 October 2026
- From Proposal to Verified Effect: Praxa, an Evidence-Bound Harness for Governed AI Agent Execution2 October 2026
- What Do Rationales Communicate? A Message-Intervention Study in Role-Specialized QA2 October 2026
- Measuring the Microtask Eligibility Gap: When Is an Off-the-Shelf SLM Enough for an Agent Harness?2 October 2026
This content is for informational purposes only and is not professional advice. Specifications, prices, plan tiers, and features change frequently and may differ from what is shown here; verify current details on the manufacturer's or company's official page before purchasing. Ratings are based on analysis of published documentation, not independent lab testing.