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LLMs can shift their representation of truth based on partner assertions, revealing a nuanced form of sycophancy that challenges our understanding of model reliability.
Coding agents may boost productivity, but they risk diminishing developers' understanding and long-term coding skills.
LLMs, unlike humans, fail to exhibit rhetorical diversity in question answering, even when explicitly prompted to mimic specific community guidelines.
