# LeapLabTHU/Simple-WAM

> Official implementation of a study on what makes world action models generalize, with an empirical study of test-time future modeling. Includes training and evaluation code on LIBERO and RoboTwin benchmarks.

- Magnitude: 0.4 out of 10 — Cooling
- Stars: 62 total · +0 stars today, ≈ 1 by evening
- Star trust: star growth looks organic
- Category: Science & research · Language: Python · Created: 2026-09-28 · Last push: 2026-09-30
- GitHub: https://github.com/LeapLabTHU/Simple-WAM · Page: https://gitnova.dev/en/r/LeapLabTHU/Simple-WAM

## Useful for

- Evaluate checkpoints on the LIBERO benchmark using run_libero_manager.py
- Run task-generalization evaluation on held-out LIBERO suites with taskgen suffixes
- Test model robustness to image corruptions on LIBERO-plus

## Why it’s here

- The repository is 4 days old and already has 62 stars. With less than two weeks of history, there's no usual pace to compare the spike against yet.
- Top new repositories this week: #188.

## Star trust

Star growth looks organic.

Star-trust labels are heuristics based on the repository’s behavior, not a check of every stargazer.

## Numbers

- Forks: 1
- Issues and pull requests: 0
- Watchers: 1
- Average over the last week: 13 per day
- Usual pace: too little history (under two weeks)
- Stars in the last hour (measured): 0

## Stars per day, last 6 days (oldest → newest, today is partial)

2026-09-27 … 2026-10-02: 0, 0, 45, 16, 1, 0

## Spotted in now

- Top new repositories this week: #188

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Magnitude (0–10) measures how fast and how unusually interest in a repository is growing right now. It is not a quality score.
Days are UTC. “So far today” is a fact; “expected by the end of the day” is a forecast.
Summaries and use cases are written by an LLM (DeepSeek V4.1 Flash) from the README and may be inaccurate: verify specific claims (benchmarks, speed, hardware) in the repository itself.
Data as of 2026-10-02 03:05 UTC, updated every 30 minutes.