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showlab/Awesome-Multimodal-Embodied-Agent

Survey on Multimodal Embodied Agents: Computer-Use → Robot-Use

#Curated list
Visit GitHub
136
7
11 contributors
Creative Commons Zero v1.0 Universal
website
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Momentum

How fast showlab/Awesome-Multimodal-Embodied-Agent is gaining stars, and where it lands on Trendshift and GitHub Trending

Activity and trending

Stars, forks and merged pull requests each day or month, lined up with the repository's rank on Trendshift Trending

Sep 10 – Oct 21, 2026

Stars +121 in 42 days

0102030
27

Forks +7 in 42 days

01
1

Merged PRs 5 in 42 days

012
2

Trendshift Trendingwhere the repository ranked each day it made the top 25

Not in the Trendshift top 25 in this period

Sep 10Sep 16Sep 22Sep 28Oct 4Oct 10Oct 16
The left and right arrow keys step from day to day; Home and End go to the first and the last

Stars, forks, merged pull requests and Trendshift Trending rank, by day
DayStars gainedForks gainedMerged PRs
Thu, Sep 10, 2026+0+00
Fri, Sep 11, 2026+27+12
Sat, Sep 12, 2026+7+00
Sun, Sep 13, 2026+2+00
Mon, Sep 14, 2026+7+10
Tue, Sep 15, 2026+6+00
Wed, Sep 16, 2026+1+10
Thu, Sep 17, 2026+1+01
Fri, Sep 18, 2026+1+00
Sat, Sep 19, 2026+0+00
Sun, Sep 20, 2026+0+00
Mon, Sep 21, 2026+0+10
Tue, Sep 22, 2026+3+10
Wed, Sep 23, 2026+0+00
Thu, Sep 24, 2026+0+00
Fri, Sep 25, 2026+0+00
Sat, Sep 26, 2026+0+00
Sun, Sep 27, 2026+0+00
Mon, Sep 28, 2026+1+00
Tue, Sep 29, 2026+0+00
Wed, Sep 30, 2026+1+00
Thu, Oct 1, 2026+1+00
Fri, Oct 2, 2026+0+00
Sat, Oct 3, 2026+0+10
Sun, Oct 4, 2026+0+00
Mon, Oct 5, 2026+0+00
Tue, Oct 6, 2026+0+00
Wed, Oct 7, 2026+0+00
Thu, Oct 8, 2026+1+01
Fri, Oct 9, 2026+5+00
Sat, Oct 10, 2026+0+00
Sun, Oct 11, 2026+0+00
Mon, Oct 12, 2026+0+00
Tue, Oct 13, 2026+3+10
Wed, Oct 14, 2026+3+01
Thu, Oct 15, 2026+7+00
Fri, Oct 16, 2026+6+00
Sat, Oct 17, 2026+1+00
Sun, Oct 18, 2026+7+00
Mon, Oct 19, 2026+13+00
Tue, Oct 20, 2026+8+00
Wed, Oct 21, 2026+9+00
Total+121+75
  • 1#1 on the list
  • 7Rank that day
  • Not trending

Social mentions

Recent discussions about this repository across the web
  1. Sep 111 post

    • [4/5] We also analyze 64 benchmarks across MMA, MMEA, and robotic systems. One clear gap: evaluation is heavily centered on Act. Only 5/64 explicitly evaluate Anticipate, and 3/64 explicitly evaluate…

      Read full on X, posted by @Anno_YanzheChen

      @Anno_YanzheChen · x.com

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