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Introspective-Diffusion/ORL

ORL: On-Policy Residual Learning for Diffusion Language Models

#LLM training
Visit GitHub
Python
23
5
1 contributors
MIT License
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Momentum

How fast Introspective-Diffusion/ORL 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

Oct 14 – Oct 26, 2026

Stars +19 in 13 days

0510
8

Forks +5 in 13 days

024
4

Merged PRs 0 in 13 days

01

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

Not in the Trendshift top 25 in this period

Oct 14Oct 16Oct 18Oct 20Oct 22Oct 24Oct 26
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
Wed, Oct 14, 2026+0+00
Thu, Oct 15, 2026+1+00
Fri, Oct 16, 2026+8+40
Sat, Oct 17, 2026+4+00
Sun, Oct 18, 2026+1+10
Mon, Oct 19, 2026+2+00
Tue, Oct 20, 2026+1+00
Wed, Oct 21, 2026+0+00
Thu, Oct 22, 2026+0+00
Fri, Oct 23, 2026+1+00
Sat, Oct 24, 2026+1+00
Sun, Oct 25, 2026+0+00
Mon, Oct 26, 2026+0+00
Total+19+50
  • 1#1 on the list
  • 7Rank that day
  • Not trending

Social mentions

Recent discussions about this repository across the web
  1. Oct 151 post

    • Result 5: fast on real hardware, even consumer GPUs. ORL cuts the number of forward passes, and NVFP4 makes each pass cheaper, so the two compose. On one B200, NVFP4 is 2.3–2.9× faster than BF16 on…

      Read full on X, posted by @Chenfeng_X

      @Chenfeng_X · x.com

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