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openai/Video-Pre-Training
默认分支 main · commit 095519fb · 扫描时间 2026/6/26 10:42:21
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下方为分数趋势(含全部就绪扫描;左旧右新,可横向滚动)。表格明细默认折叠,展开后每页 10 条,最新在上。
共 3 条就绪扫描。点击下方按钮展开表格(每页 10 条,可翻页)。
行动计划告诉你下一步要做什么——按影响力排序、可直接复制粘贴的修改。品类可见性是真正的 GEO 测试:当用户向 AI 提一个不带品牌、本应让 openai/Video-Pre-Training 浮出水面的问题时,AI 是真的推荐了你,还是推荐了你的竞品?客观检查验证 AI 引擎最先权衡的那些元数据信号。自指检查判断 AI 是否还认识你的名字。
行动计划 — 可复制粘贴的修复
2 条由 gemini-2.5-flash 生成、按优先级排序的修改。修完后请把对应条目标记为完成。
- mediumhomepage#1Add a homepage URL to the repository's About section
原因:
复制粘贴的修复https://openai.com/research/video-pretraining
- mediumreadme#2Expand the README's introductory paragraph to clarify the project's core purpose
原因:
当前# Video-Pre-Training Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos > :page_facing_up: Read Paper \ :mega: Blog Post \ :space_invader: MineRL Environment (note version 1.0+ required) \ :checkered_flag: MineRL BASALT Competition # Running agent models
复制粘贴的修复# Video-Pre-Training Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos This repository provides the code and models for Video PreTraining (VPT), a method that enables training high-performing AI agents by leveraging vast amounts of unlabeled online video data. Specifically, VPT demonstrates how agents can learn complex behaviors in environments like Minecraft through self-supervised learning from human demonstrations, without requiring explicit reward signals. > :page_facing_up: Read Paper \ :mega: Blog Post \ :space_invader: MineRL Environment (note version 1.0+ required) \ :checkered_flag: MineRL BASALT Competition # Running agent models
本次扫描解析到的品类 GEO 通道:google/gemini-2.5-flash, deepseek/deepseek-v4-flash
品类可见性 — 真正的 GEO 测试
向 google/gemini-2.5-flash 提出的不带品牌问题。AI 推荐了你,还是推荐了别人?
各模型使用同一组问题 — 切换标签对比回答与排名。
- Diffusion Policy · 被推荐 1 次
- Perceiver IO · 被推荐 1 次
- R3M · 被推荐 1 次
- BC-Z · 被推荐 1 次
- Contrastive Learning Frameworks · 被推荐 1 次
- 品类问题How can I train an AI agent to perform tasks using only unlabeled video demonstrations?你:未被推荐AI 推荐顺序:
- Diffusion Policy
- Perceiver IO
- R3M
- BC-Z
- Contrastive Learning Frameworks
- VideoMAE
- DreamerV3
AI 推荐了 7 个替代方案,却始终没点名 openai/Video-Pre-Training。这就是要补上的差距。
查看 AI 完整回答
- 品类问题What tools enable training reinforcement learning agents from large datasets of observed human behavior?你:未被推荐AI 推荐顺序:
- Hugging Face TRL
- Stable Baselines3
- RLlib
- D4RL
- AWR
- Behavioral Cloning
- Hugging Face Transformers
- Keras
AI 推荐了 8 个替代方案,却始终没点名 openai/Video-Pre-Training。这就是要补上的差距。
查看 AI 完整回答
客观检查
针对 AI 引擎最看重的元数据信号的规则审计。
- Metadata completenesswarn
建议:
- README presencepass
自指检查
当被直接问到你时,AI 是否还知道你的仓库存在?
- Compared to common alternatives in this category, what is the core differentiator of openai/Video-Pre-Training?passAI 明确点名了 openai/Video-Pre-Training
AI 的回答可能信誓旦旦却是错的。请按事实核对:技术栈、目标人群、差异化点是不是和你实际的对得上?
- If a team adopts openai/Video-Pre-Training in production, what risks or prerequisites should they evaluate first?passAI 明确点名了 openai/Video-Pre-Training
AI 的回答可能信誓旦旦却是错的。请按事实核对:技术栈、目标人群、差异化点是不是和你实际的对得上?
- In one sentence, what problem does the repo openai/Video-Pre-Training solve, and who is the primary audience?passAI 明确点名了 openai/Video-Pre-Training
AI 的回答可能信誓旦旦却是错的。请按事实核对:技术栈、目标人群、差异化点是不是和你实际的对得上?
嵌入你的 GEO 徽章
把这个徽章贴进 openai/Video-Pre-Training 的 README。每次重新扫描都会自动更新,并跳到最新报告——是「我在乎 AI 可发现性」最简单的公开证明。
[](https://repogeo.com/zh/r/openai/Video-Pre-Training)<a href="https://repogeo.com/zh/r/openai/Video-Pre-Training"><img src="https://repogeo.com/badge/openai/Video-Pre-Training.svg" alt="RepoGEO" /></a>订阅 Pro,解锁深度诊断
openai/Video-Pre-Training — 轻量扫描仍免费;本卡列出 Pro 相对轻量的深度额度。
- 深度报告每月 10 次
- 无品牌品类查询5,轻量 2
- 优先行动项8,轻量 3