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kuleshov-group/setdlms

[ICML 2026] Set Diffusion: Interpolating Token Orderings between Autoregression and Diffusion for Fast and Flexible Decoding

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Python
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3
1 contributors
MIT License
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Momentum

How fast kuleshov-group/setdlms 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 26, 2026

Stars +1 in 47 days

01
1

Forks +0 in 47 days

01

Merged PRs 0 in 47 days

01

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 16Oct 22
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+1+00
Fri, Sep 11, 2026+0+00
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Mon, Sep 14, 2026+0+00
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Total+1+00
  • 1#1 on the list
  • 7Rank that day
  • Not trending

Social mentions

Recent discussions about this repository across the web
  1. Jul 32 posts

    • ✅ KV Caching: Set Diffusion caches KVs after each generated set. This is more efficient than Block Diffusion, which waits until block completion. ✅ Arbitrary-Length Generation: Sequential set…

      Read full on X, posted by @mariannearr

      @mariannearr · x.com

    • ✅ KV Caching: Set Diffusion caches KVs after each generated set, unlike Block Diffusion, which waits until full block completion ✅ Arbitrary-Length Generation: Sequential set modeling enables…

      Read full on X, posted by @mariannearr

      @mariannearr · x.com

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