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vijayabhaskar-ev/dreamer_v4

Code, results and checkpoints for the paper "Silent Pipeline Defects in World-Model RL: A Dreamer 4 Case Study": a PyTorch reimplementation of Dreamer 4, two silent defects that passed 12 checks, and three cheap checks that catch them

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Python
39
2
2 contributors
MIT License
website
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Momentum

How fast vijayabhaskar-ev/dreamer_v4 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 21 – Oct 31, 2026

Stars +1 in 41 days

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1

Forks +0 in 41 days

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Merged PRs 0 in 41 days

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

Not in the Trendshift top 25 in this period

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The left and right arrow keys step from day to day; Home and End go to the first and the last

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  • 1#1 on the list
  • 7Rank that day
  • Not trending

Social mentions

Recent discussions about this repository across the web
  1. Jun 242 posts

    • Reproduced DreamerV4 from scratch (PyTorch); offline imagination-RL ≈ behavior cloning in closed-loop eval — here's the teardown

      Read full on Reddit

      r/reinforcementlearning

    • The one rule that matters at deployment: SAMPLE the actor, don't argmax it. It was trained on sampled actions (PMPO optimizes the sampled policy), so any deterministic readout is off-distribution and…

      Read full on X, posted by @vijayabhaskarev

      @vijayabhaskarev · x.com

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