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Платформа FinRobot для финансовых AI-агентов: открытый источник с поддержкой LLMs

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Достижение баланса в обучении на протяжении всей жизни: подход WISE к запоминанию

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Как синтетические доказательства меняют возможности LLM: революционные изменения.

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Обзор развития моделей семьи Клода от Anthropic AI

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Оценка обнаружения аномалий во временных рядах: метод близости для оценки аномалий во временных рядах

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Лучшие курсы по структурам данных и алгоритмам

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Фреймворк LANISTR: обучение на языковых, изображенческих и структурированных данных с использованием внимания AI.

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Как настроить GPT-3.5 для эффективных писем с предложениями

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Как Language Agents переводят длинные романы?

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Новая функция загрузки таблиц в Google Gemini 1.5 Pro для улучшения анализа данных

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Новый Vision Transformer от Microsoft Research для цифровой патологии

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Инструмент для оценки языковых моделей от EleutherAI: lm-eval для надежной оценки NLP

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Оценка цепочек рассуждений для точных решений в области LLM: за пределами игры частотности

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Изменение подхода: роль MoRA в развитии эффективных техник точной настройки параметров

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Объединенная мультимодальная модель на базе архитектуры Sparse MoE

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Исследование из Университета Чикаго: финансовый анализ с помощью больших языковых моделей

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Улучшение понимания и производительности нейронной сети с помощью волнового интегрированного сети Колмогорова-Арнольди (Wav-KAN)

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Прозрачность в фондовых моделях: следующий шаг в индексе прозрачности фондовых моделей (FMTI)

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Интерфейс командной строки Elia для взаимодействия с LLM.

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Исследователи MIT предлагают Cross-Layer Attention (CLA): модификацию архитектуры трансформера, которая уменьшает размер кэша Key-Value (KV) путем совместного использования активаций KV между слоями.

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