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JethroJames/awesome-robots-icl

Companion repository for “In-Context Learning for Robots: Methods and Applications” — methods, datasets, and benchmarks organized by taxonomy and release date.

#Curated list
Visit GitHub
Python
162
2 contributors
MIT License
website
FeaturedAdvertise to 180K+ monthly visitors
ClawBench

a benchmark for personal agents

Bifrost

Enterprise AI Gateway Built For Scale: Route, Govern, and Secure All Your AI Traffic

Momentum

How fast JethroJames/awesome-robots-icl 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 29 – Oct 24, 2026

Stars +152 in 26 days

01020
17

Forks +0 in 26 days

01

Merged PRs 3 in 26 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 29Oct 3Oct 7Oct 11Oct 15Oct 19Oct 23
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
Tue, Sep 29, 2026+0+00
Wed, Sep 30, 2026+2+01
Thu, Oct 1, 2026+3+02
Fri, Oct 2, 2026+1+00
Sat, Oct 3, 2026+0+00
Sun, Oct 4, 2026+0+00
Mon, Oct 5, 2026+1+00
Tue, Oct 6, 2026+1+00
Wed, Oct 7, 2026+1+00
Thu, Oct 8, 2026+0+00
Fri, Oct 9, 2026+2+00
Sat, Oct 10, 2026+1+00
Sun, Oct 11, 2026+1+00
Mon, Oct 12, 2026+2+00
Tue, Oct 13, 2026+17+00
Wed, Oct 14, 2026+7+00
Thu, Oct 15, 2026+12+00
Fri, Oct 16, 2026+14+00
Sat, Oct 17, 2026+6+00
Sun, Oct 18, 2026+16+00
Mon, Oct 19, 2026+15+00
Tue, Oct 20, 2026+13+00
Wed, Oct 21, 2026+13+00
Thu, Oct 22, 2026+8+00
Fri, Oct 23, 2026+10+00
Sat, Oct 24, 2026+6+00
Total+152+03
  • 1#1 on the list
  • 7Rank that day
  • Not trending

Social mentions

Recent discussions about this repository across the web
  1. Sep 301 post
    • In-Context Learning for Robots A 100-page survey with 412 references organizes robot ICL into four method families: context-conditioned policies, geometric demonstration transfer, world-model-based…

      Read full on X, posted by @HuggingPapers

      @HuggingPapers · x.com

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