An important direction for future research is understanding why default language models exhibit this confirmatory sampling behavior. Several mechanisms may contribute. First, instruction-following: when users state hypotheses in an interactive task, models may interpret requests for help as requests for verification, favoring supporting examples. Second, RLHF training: models learn that agreeing with users yields higher ratings, creating systematic bias toward confirmation [sharma_towards_2025]. Third, coherence pressure: language models trained to generate probable continuations may favor examples that maintain narrative consistency with the user’s stated belief. Fourth, recent work suggests that user opinions may trigger structural changes in how models process information, where stated beliefs override learned knowledge in deeper network layers [wang_when_2025]. These mechanisms may operate simultaneously, and distinguishing between them would help inform interventions to reduce sycophancy without sacrificing helpfulness.
Акции компании Adidas упали сразу на семь процентов после того, как был опубликован прогноз прибыли этого спортивного гиганта на 2026 год. Об этом сообщило Reuters.
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It’s possible, however, to report on all this while also staying optimistic about the underlying technology–whether it be crypto, AI, self-driving cars, or the many other marvelous inventions that can improve our lives. Unfortunately, it feels that expressing views on technology has become yet another way to declare allegiance with one side or the other in our interminable culture wars. This is a shame. New technology, whether in the form of electricity or antibiotics or the internet, has always brought cause for excitement and the promise of a better future.
Иран установил личности виновных в ударе по школе для девочек в Минабе14:56
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