# Researchers test duplicate filtering to reduce false claims accepted by AI judges

_Published Monday, November 9, 2026 at 2:05 AM EST · AI, Science · Latest · Tier 2 — Notable_

Researchers report in an arXiv preprint that filtering copied news reports reduced false claims accepted by AI judges in a simulated continual-learning stream. Showing judges one report per detected copy chain cut acceptance of copied lies by 0.10-0.24 across four judges, at a mean cost of no more than 4.2 percentage points of accepted truths.

The study examined 200,000 English CC-News articles and linked 18.9% to a near-copy from another outlet. Its initial detector missed all tested LLM rewrites. A separate test using named entities reduced acceptance of reworded-copy lies from 0.67 to 0.20, or 0.40 when rewrites invented details. Colluding sources remain an open problem.

## Sources

- [cs.CL updates on arXiv.org](https://arxiv.org/abs/2611.09203)

---
Canonical: https://techandbusiness.org/newswire/sF3BNcjcpbdvzv8NJI7W0x
Published: 2026-11-09T07:05:49.573Z
Story chronology: 2026-11-09T05:00:00.000Z
Retrieved: 2026-11-09T10:09:27.748Z
Publisher: Tech & Business (techandbusiness.org)