// 步骤4：扩展左边界（向左找所有minVal的元素，全程不越界）
In recent years, LLMs have shown significant improvements in their overall performance. When they first became mainstream a couple of years before, they were already impressive with their seemingly human-like conversation abilities, but their reasoning always lacked. They were able to describe any sorting algorithm in the style of your favorite author; on the other hand, they weren't able to consistently perform addition. However, they improved significantly, and it's more and more difficult to find examples where they fail to reason. This created the belief that with enough scaling, LLMs will be able to learn general reasoning.
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Снежная и морозная зима не гарантирует избавление от испанских слизней в теплое время года. Вероятность их нашествия на российские огороды оценил руководитель сегмента «Умные цепи» поставок рабочей группы FoodNet (Фуднет) НТИ Сергей Косогор в разговоре с агентством РИА Новости.