REPOGEO REPORT · LITE

openai/Video-Pre-Training

Default branch main · commit 095519fb · scanned 6/26/2026, 10:42:21 AM

GitHub: 1,714 stars · 171 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

35 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 1 warn · 0 fail

Objective metadata checks

AI knows your name

3 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface openai/Video-Pre-Training, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

mediumhomepage#1
Add a homepage URL to the repository's About section
Why:
COPY-PASTE FIX
```
https://openai.com/research/video-pretraining
```

mediumreadme#2

Expand the README's introductory paragraph to clarify the project's core purpose

Why:

CURRENT

# 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

COPY-PASTE FIX

# 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

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall

0 / 2

0% of queries surface openai/Video-Pre-Training

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Diffusion Policy

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Diffusion Policy · recommended 1×
Perceiver IO · recommended 1×
R3M · recommended 1×
BC-Z · recommended 1×
Contrastive Learning Frameworks · recommended 1×

CATEGORY QUERY
How can I train an AI agent to perform tasks using only unlabeled video demonstrations?
you: not recommended
AI recommended (in order):
1. Diffusion Policy
2. Perceiver IO
3. R3M
4. BC-Z
5. Contrastive Learning Frameworks
6. VideoMAE
7. DreamerV3
AI recommended 7 alternatives but never named openai/Video-Pre-Training. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What tools enable training reinforcement learning agents from large datasets of observed human behavior?
you: not recommended
AI recommended (in order):
1. Hugging Face TRL
2. Stable Baselines3
3. RLlib
4. D4RL
5. AWR
6. Behavioral Cloning
7. Hugging Face Transformers
8. Keras
AI recommended 8 alternatives but never named openai/Video-Pre-Training. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
warn
Suggestion:
README presence
pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

Compared to common alternatives in this category, what is the core differentiator of openai/Video-Pre-Training?
pass
AI named openai/Video-Pre-Training explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts openai/Video-Pre-Training in production, what risks or prerequisites should they evaluate first?
pass
AI named openai/Video-Pre-Training explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
In one sentence, what problem does the repo openai/Video-Pre-Training solve, and who is the primary audience?
pass
AI named openai/Video-Pre-Training explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/openai/Video-Pre-Training.svg)](https://repogeo.com/en/r/openai/Video-Pre-Training)

HTML

<a href="https://repogeo.com/en/r/openai/Video-Pre-Training"><img src="https://repogeo.com/badge/openai/Video-Pre-Training.svg" alt="RepoGEO" /></a>

Pro

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openai/Video-Pre-Training — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite