Archive: The Mirroring Effect
The "Mirroring Effect" refers to the tendency of Large Language Models (LLMs) to adopt the persona, tone, and biases of the user's prompt (sycophancy).
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Seminal Paper
Sycophancy in AI Models
Sharma et al. (2023)
Demonstrates that RLHF-tuned models often agree with user statements even when they are factually incorrect.
The Waluigi Effect
Cleo Nardo (2023)
Proposes that forcing an LLM to be perfectly aligned creates a latent "shadow persona" that is easily jailbroken.
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2026 Perspective
Recursive Persona Collapse in GPT-6
AIS Research (2025)
Analysis of how extended context windows (10M+) cause models to permanently adopt user bias after 50 turns.