# leofan90/Awesome-World-Models

A comprehensive list of papers for the definition of World Models and using World Models for General Video Generation, Embodied AI, and Autonomous Driving, including papers, codes, and related websites.

Repository: https://github.com/leofan90/Awesome-World-Models
Canonical: https://ross.abutalabs.com/products/leofan90-awesome-world-models
Language: Python
License: BSD-3-Clause
License Family: permissive
Topics: artificial-intelligence, autonomous-driving, awesome, deep-learning, embodied-ai, future-prediction, video-prediction, world-model
Last push: 2026-08-26T04:12:48+00:00

## Health v2 (maintenance only)
Score: 66/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 35, longevity 47
- inputs: {"age_days": 662, "days_push": 7, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1985, forks 74 (observed 2026-08-28T04:06:02.649992+00:00)

## What it is
A curated awesome-list of research papers, code, and websites on World Models, covering general video generation, embodied AI, VLA, visual understanding, and autonomous driving. It serves as a reading and reference index rather than executable software.

## Use cases
- find papers on world models for robotics
- survey world models for autonomous driving
- research video prediction and future prediction models
- find world model code implementations
- keep up with new world model research
- prepare a literature review on embodied AI world models

## When to choose
- you need a curated, categorized index of world model papers and resources
- you are researching embodied AI, robotics, or autonomous driving world models
- you want links to papers, code, and project websites in one place

## When to avoid
- you need runnable software or a library to integrate into your project
- you need a dataset rather than a paper list
- you need an exhaustive, non-curated paper search engine

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation
- domain: artificial-intelligence, deep-learning, autonomous-vehicles, robotics, awesome-lists
- platform: python
- tags: awesome-list, world-models, video-prediction, embodied-ai, research-papers, curated-list

## Member repositories
- leofan90/Awesome-World-Models (main) score 66

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:02.649992+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:03:17.250282+00:00, confidence not recorded.
  - readme: https://github.com/leofan90/Awesome-World-Models (fetched 2026-08-28T04:06:02.649992+00:00, sha db85e15a569a)
- Data as of 2026-08-30T08:39:29.467469+00:00.