REPOGEO REPORT · LITE

OpenDriveLab/DriveLM

Default branch main · commit 1de72a74 · scanned 5/8/2026, 7:19:23 PM

GitHub: 1,306 stars · 86 forks

AI VISIBILITY SCORE

40 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

2 pass · 0 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 OpenDriveLab/DriveLM, 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

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

OVERALL DIRECTION

highreadme#1

Add a concise positioning statement immediately after the main title in README

Why:

CURRENT

**DriveLM:Driving with **G**raph **V**isual **Q**uestion **A**nswering*

`Autonomous Driving Challenge 2024` **Driving-with-Language** Leaderboard.

COPY-PASTE FIX

**DriveLM:Driving with **G**raph **V**isual **Q**uestion **A**nswering*
An end-to-end autonomous driving framework leveraging Graph VQA for advanced perception, prediction, and planning.

`Autonomous Driving Challenge 2024` **Driving-with-Language** Leaderboard.

mediumtopics#2

Expand topics to include more specific autonomous driving system terms

Why:

CURRENT

autonomous-driving, chain-of-thought, graph-of-thoughts, large-language-models, llm, prompt-engineering, prompting, tree-of-thoughts, vision-language

COPY-PASTE FIX

autonomous-driving, autonomous-vehicles, driving-agent, end-to-end-driving, chain-of-thought, graph-of-thoughts, large-language-models, llm, prompt-engineering, prompting, tree-of-thoughts, vision-language

mediumabout#3

Refine the GitHub description to emphasize 'framework' and 'end-to-end'

Why:

CURRENT

[ECCV 2024 Oral] DriveLM: Driving with Graph Visual Question Answering

COPY-PASTE FIX

[ECCV 2024 Oral] DriveLM: An end-to-end autonomous driving framework powered by Graph Visual Question Answering.

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 OpenDriveLab/DriveLM

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

GPT-4o

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

GPT-4o · recommended 1×
Gemini 1.5 Pro · recommended 1×
Llama 3 · recommended 1×
CLIP · recommended 1×
Llama 2 · recommended 1×

CATEGORY QUERY
Seeking VLM solutions for complex reasoning and decision-making in autonomous driving systems.
you: not recommended
AI recommended (in order):
1. GPT-4o
2. Gemini 1.5 Pro
3. Llama 3
4. CLIP
5. Llama 2
6. Mixtral
7. OWL-ViT
AI recommended 7 alternatives but never named OpenDriveLab/DriveLM. This is the gap to close.
Show full AI answer
CATEGORY QUERY
How to apply graph visual question answering for autonomous vehicle perception and control?
you: not recommended
AI recommended (in order):
1. OpenPCDet (open-mmlab/OpenPCDet)
2. Mask R-CNN
3. RelTR (microsoft/RelTR)
4. SGTR (microsoft/SGTR)
5. DGL (Deep Graph Library) (dmlc/dgl)
6. PyTorch Geometric (PyG) (pyg-team/pytorch_geometric)
7. Neo4j (neo4j/neo4j)
8. GQA (Graph Question Answering) Dataset & Models
9. ViLBERT (facebookresearch/vilbert)
10. LXMERT (unc-nlp/LXMERT)
11. Hugging Face Transformers (huggingface/transformers)
12. ROS (Robot Operating System) (ros/ros)
13. Apollo (Baidu's Autonomous Driving Platform) (ApolloAuto/apollo)
14. CARLA (Simulator for Autonomous Driving) (carla-simulator/carla)
AI recommended 14 alternatives but never named OpenDriveLab/DriveLM. This is the gap to close.
Show full AI answer

Objective checks

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

Metadata completeness
pass
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 OpenDriveLab/DriveLM?
pass
AI named OpenDriveLab/DriveLM explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts OpenDriveLab/DriveLM in production, what risks or prerequisites should they evaluate first?
pass
AI named OpenDriveLab/DriveLM 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 OpenDriveLab/DriveLM solve, and who is the primary audience?
pass
AI named OpenDriveLab/DriveLM explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of OpenDriveLab/DriveLM. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/OpenDriveLab/DriveLM.svg)](https://repogeo.com/en/r/OpenDriveLab/DriveLM)

HTML

<a href="https://repogeo.com/en/r/OpenDriveLab/DriveLM"><img src="https://repogeo.com/badge/OpenDriveLab/DriveLM.svg" alt="RepoGEO" /></a>

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OpenDriveLab/DriveLM — 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