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A comprehensive TypeScript-based platform that revolutionizes AI-assisted development through intelligent prompt template management, optimization, and execution. Built for enterprise teams, ...

Utilize AI to analyze application runtime data (e.g., rendering time, communication latency), obtain optimization suggestions (such as reducing component re-rendering, reusing hardware connections), ...

Abstract: This paper presents an automatic evaluation framework based on Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM) architecture for objective motion assessment. Traditional ...

Abstract: Recent advancements in scaling large language models (LLMs) have enhanced various natural language processing (NLP) tasks. However, open-source moderately sized models, such as BERT, are ...

In this tutorial, we shift from traditional prompt crafting to a more systematic, programmable approach by treating prompts as tunable parameters rather than static text. Instead of guessing which ...

Have you ever stared at a blank screen, trying to craft the perfect AI prompt, only to feel like you’re overcomplicating something that should be simple? For anyone who’s dabbled in prompt engineering ...

SCOPE transforms static agent prompts into self-evolving systems that learn from their own execution. Instead of manually crafting prompts, SCOPE automatically synthesizes guidelines from execution ...

Given a task in the form of a basic description and its training examples, prompt optimization is the problem of synthesizing the given information into a text prompt for a large language model (LLM).