awesome-repositories.com
المدونة
awesome-repositories.com

اكتشف أفضل مستودعات المصادر المفتوحة باستخدام بحث مدعوم بالذكاء الاصطناعي.

استكشفعمليات بحث منسقةبدائل مفتوحة المصدربرمجيات ذاتية الاستضافةالمدونةخريطة الموقع
المشروعحولكيفية ترتيب النتائجالصحافةخادم MCP
قانونيالخصوصيةالشروط
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·

2 مستودعات

Awesome GitHub RepositoriesSuccess-Based Parallel Sampling

Mechanisms for spawning concurrent task attempts to merge and select the most successful outcome.

Distinct from Parallel Task Spawning: Distinct from general spawning by its focus on outcome selection for optimization.

Explore 2 awesome GitHub repositories matching software engineering & architecture · Success-Based Parallel Sampling. Refine with filters or upvote what's useful.

Awesome Success-Based Parallel Sampling GitHub Repositories

اعثر على أفضل المستودعات باستخدام الذكاء الاصطناعي.سنبحث عن أفضل المستودعات المطابقة باستخدام الذكاء الاصطناعي.
  • caolan/asyncالصورة الرمزية لـ caolan

    caolan/async

    28,150عرض على GitHub↗

    Async is a JavaScript asynchronous flow library designed to manage the execution and coordination of asynchronous tasks in Node.js and the browser. It provides functional utilities to wrap, process, and orchestrate complex asynchronous workflows. The library distinguishes itself through a comprehensive task orchestrator that handles dependency graphs to resolve circular references and manages concurrent task queues. It includes a unification bridge that allows callback-style and promise-based functions to operate within the same execution interface. The project covers several primary capabil

    Executes multiple tasks in parallel and returns success as soon as any single task completes successfully.

    JavaScript
    عرض على GitHub↗28,150
  • simular-ai/agent-sالصورة الرمزية لـ simular-ai

    simular-ai/Agent-S

    11,855عرض على GitHub↗

    Agent-S is a multimodal AI agent and LLM desktop automation framework designed to control operating systems through graphical user interface interactions. It functions as a computer use interface, utilizing vision-language grounding to translate natural language goals into precise screen coordinates and system actions. The project differentiates itself by combining structured accessibility tree inspection with vision-based element localization. It manages cross-application workflows by mapping conceptual descriptions to physical pixels and simulating low-level keyboard and mouse events to mov

    Executes multiple task attempts in parallel to select the most successful outcome.

    Pythonagent-computer-interfaceai-agentscomputer-automation
    عرض على GitHub↗11,855
  1. Home
  2. Software Engineering & Architecture
  3. Task Scheduling
  4. Parallel Task Executors
  5. Parallel Task Spawning
  6. Success-Based Parallel Sampling