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LLM Sycophancy: A Galois Closure Limitation

Large Language Models (LLMs) often respond within a user's belief space, creating a closed loop where no new information enters. This sycophancy can be formalized as a Galois closure, limiting the models' ability to provide unbiased responses. The closure condition prevents LLMs from breaking free from users' prior beliefs, potentially widening the intellectual access gap.

Mathematics & logic, Mathematics, Mathematical Logic