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DaWin: Безобученная система динамической интерполяции весов для надежной адаптации

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Исследователи Стэнфорда предложили новое улучшение для Vision Transformers: локальная выравниваемость.

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Оценка уязвимостей агентов LLM: стандарт AgentHarm для защиты от атак взлома

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IBM представила ST-WebAgentBench: новый стандарт для оценки безопасности и надежности веб-агентов

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OpenAI представила приложение ChatGPT для Windows

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Jina AI представила g.jina.ai: мощный API для улучшения текстов с помощью фактической информации из реального времени.

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Выпуск PyTorch 2.5: Повышение эффективности и масштабируемости машинного обучения

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Katanemo открывает доступ к своей функции: набор больших языковых моделей с обещанием высокой скорости выполнения задач.

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Как большие языковые модели могут одновременно выполнять разные задачи обучения в контексте.

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От ONNX до статических векторов: Почему Sentence Transformers v3.2.0 важное обновление?

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Исследователи Google AI предложили «МОДЕЛЬНЫЕ РОИ»: алгоритм совместного поиска для адаптации различных экспертов LLM к широкому спектру задач.

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CodeJudge: Фреймворк машинного обучения для оценки генерации кода без тестовых случаев.

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Предложение AI-рамки для защиты мобильных услуг от атак злоумышленников

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IoT-LLM: ИИ-система для улучшения восприятия и мышления с помощью данных датчиков IoT

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Meissonic: Модель для создания высококачественных изображений из текста без автоподстройки

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Nvidia запускает Nemotron 70B, обгоняя GPT-4 от OpenAI по многим показателям.

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Анализ обманных атак на данные с помощью противостоящего машинного обучения для прогнозирования солнечной энергетики

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Риски использования синтетических данных для обучения больших языковых моделей по данным Meta AI

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Познакомьтесь с TurtleBench: Уникальная система оценки ИИ для анализа языковых моделей с помощью реальных задач “Да/Нет”.

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Дифференцируемое адаптивное объединение: новый подход ИИ к интеграции моделей

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