# Self‑Debiasing Prompts Boost LLM Judges' Reliability

> Researchers show that simple prompts can help language‑model judges reduce bias without extra training.

Oossa · 2026-10-20 · https://oossa.com/en/self-debiasing-prompts-boost-llm-judges-reliability

A team led by Y. Yin published a paper on Oct 20, 2026, showing that large language model judges can debias themselves. They tested two tricks: a prompt that warns the model about possible bias before it judges, and a follow‑up prompt that asks the model to critique its own answer for bias. Across three state‑of‑the‑art models, the self‑debiasing prompt improved results in 20 of 21 model‑bias pairings, sometimes adding up to 15 points. The older external critic method performed worse on the new bias tests.

## The facts

- Paper published Oct 20, 2026 ("Tue Oct 20 2026 06:00:00 GMT+0200")
- Self‑debiasing improved 20 of 21 model‑bias combos, up to 15 percentage points

## Why it matters

Prompt‑based self‑debiasing could make automated AI evaluations more trustworthy for developers and researchers.

## Sources & references

1. [The Judge Can Debias Itself: Awareness and Self-Debiasing for Reliable LLM-as-a-Judge](https://arxiv.org/abs/2610.24320) – arXiv, 2026-10-20

Last updated: 2026-10-20