技能目录

为 AI Agent 发现可复用技能。

按任务搜索真实的 GitHub 技能,并在使用前查看 Stars、信任、审计、分类和安装路径。

每个推荐都保留与其仓库、审计和安装路径的明确关联。

搜索结果: neurips-2018

英文目录

Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.

18K
Stars
87/100
信任
分类: design-creative审计

SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024]

20K
Stars
87/100
信任
分类: coding-agents审计

A machine learning-based video super resolution and frame interpolation framework. Est. Hack the Valley II, 2018.

20K
Stars
86/100
信任
分类: ml-automation审计

[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.

25K
Stars
74/100
信任
分类: support-automation审计
VAR83

[NeurIPS 2024 Best Paper Award][GPT beats diffusion🔥] [scaling laws in visual generation📈] Official impl. of "Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction". An *ultra-simple, user-friendly yet state-of-the-art* codebase for autoregressive image generation!

8.7K
Stars
83/100
信任
分类: media-automation审计

[NeurIPS '25] Knowledge Graph Generation from Any Text

1.2K
Stars
72/100
信任
分类: rag-knowledge审计

rPPG-Toolbox: Deep Remote PPG Toolbox (NeurIPS 2023)

1.1K
Stars
71/100
信任
分类: robotics-iot审计

All notes and materials for the CS229: Machine Learning course by Stanford University

3.3K
Stars
71/100
信任
分类: ml-automation审计

MLNLP: This repository is a collection of AI top conferences papers (e.g. ACL, EMNLP, NAACL, COLING, AAAI, IJCAI, ICLR, NeurIPS, and ICML) with open resource code

2.7K
Stars
68/100
信任
分类: robotics-iot审计

Free open public domain football datasets in the Football.TXT format for the World Cup (incl. Canada/USA/Mexico 2026, Qatar 2022, Russia 2018, Brazil 2014, etc.) and World Cup Quali(fiers)

634
Stars
73/100
信任
分类: sports-analytics审计