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Инструмент LLMLean: советы по тактике и завершение доказательств с использованием LLM и методики Lean

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Выпущена модель Gemma 2-2B: продвинутое создание текстов, развертывание на устройстве и улучшенные безопасные функции.

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Библиотека Darts для удобного прогнозирования и обнаружения аномалий во временных рядах.

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Новый инструмент для ускорения работы больших языковых моделей на устройствах: Torchchat

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Значение модели ссылки в оптимизации прямых предпочтений: эмпирическое исследование о необходимости ограничений оптимального расхождения Кульбака-Лейблера.

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Новые методы обнаружения плотных подграфов во временных графах: JCDS и JWDS

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Новая статья от Apple о языковых моделях для функций искусственного интеллекта: AFM-on-Device и AFM-Server

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Meta AI представляет Meta Segment Anything Model 2 (SAM 2): первую универсальную модель для сегментации объектов на изображениях и видео.

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Фреймворк Baidu AI для улучшения надежности и прослеживаемости систем RAG.

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Исследование экспертного руководства и стратегических отклонений в многоагентном имитационном обучении

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6 методов статистического анализа для A/B-тестирования в науке о данных

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Лучшие курсы по TensorFlow

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Мощная библиотека Stumpy для анализа временных рядов на Python

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Новый бенчмарк для глубокого обучения на реляционных базах данных: RelBench от ученых из Стэнфорда

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Новый выпуск Zamba2-2.7B: маленькая языковая модель с удвоенной скоростью и сокращением использования памяти на 27%

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Методы оценки отказа в языковых моделях: изучение и метрики

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Библиотека PyTorch для обучения на реляционных таблицах с использованием больших языковых моделей

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Новые модели Lite-Oute-1: Lite-Oute-1-300M и Lite-Oute-1-65M – компактные, но мощные решения ИИ.

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Улучшение памяти для крупномасштабных NLP-моделей: обзор MINI-SEQUENCE TRANSFORMER

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Исследование показывает, что модель искусственного интеллекта терпит неудачу при последовательном обучении на синтетических данных.

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