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Why Large Language Models Can’t Be Trusted with the Truth
The more convincing the delivery, the easier it is to overlook the cracks in the foundation.
LLMs become most dangerous precisely when they sound most right. In information‑hungry environments, a confident error often outranks a cautious truth.

Unpacking Illusions in Language: The Risks of Trusting LLMs at Face Value
In their pursuit of coherence and plausibility, LLMs frequently generate falsehoods with convincing articulation, making their greatest technical strength a potential liability when misapplied or uncritically trusted.
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