# Research

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Peer-reviewed research from The Knowledge Company on how LLM ranking signals reshape the content ecosystems they rank, including CHASE (COLM 2026).

Peer-reviewed work on how AI search reshapes the content it ranks — published in full, so anyone can check it.

Papers

[COLM 2026](https://colm.cc/)

[arXiv:2608.30466](https://arxiv.org/abs/2608.30466)

31 Aug 2026

## [CHASE: How Content Ecosystems Are Reshaped When Ranking Is the Only Target](https://arxiv.org/abs/2608.30466)

Qianwen Gao, Zichang Su, Yiwen Hou, Arlen Kumar, Leanid Palkhouski

A controlled simulation of what happens when creators keep rewriting documents to chase an LLM ranking signal. Over twenty rounds in six domains, the documents that move closest to the ranking feature profile drift furthest from independently judged quality — and a random-target control shows the drift comes from the ranking incentive, not from rewriting alone.

Rank–citation AUC 0.853 ± 0.093 · 20 rounds · mean Spearman shift −0.068

[Abstract ↗](https://arxiv.org/abs/2608.30466)

[PDF ↗](https://arxiv.org/pdf/2608.30466)

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