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docs: adoption-focused README, WHY_FROSSL, and reproducible CIFAR-10 comparison#2

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OFSkean:mainfrom
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docs: adoption-focused README, WHY_FROSSL, and reproducible CIFAR-10 comparison#2
jacobsn wants to merge 4 commits into
OFSkean:mainfrom
mvrl:main

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@jacobsn

@jacobsn jacobsn commented Jul 6, 2026

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This PR brings the documentation improvements from the MVRL fork back to the source repo. It is a docs-only change — no code or training behavior is modified.

What's included

  • README rewrite for adoption — clearer positioning (why/when to use FroSSL), a "how does it compare?" table, and sections on faster convergence and multiview.

  • docs/WHY_FROSSL.md — a deeper comparison of the math, tradeoffs, and evidence vs SimCLR, BYOL, VICReg, and Barlow Twins.

  • Library integrations — links to the in-progress FroSSL integrations in lightly and solo-learn, so users can reach FroSSL from familiar APIs.

  • Reproducible CIFAR-10 comparison (experiments/lightly_cifar10/) — FroSSL vs seven common SSL methods run through lightly's CIFAR-10 kNN benchmark under an identical protocol on the same GPU (ResNet-18, batch 512, 200 epochs, kNN k=200):

    Method kNN Top-1 Runtime Peak GPU
    FroSSL 86.9% 52.1 min 4.83 GB
    BYOL 86.5% 62.5 min 5.43 GB
    DCL 85.0% 51.9 min 4.85 GB
    SimCLR 84.8% 51.6 min 4.85 GB
    MoCo 84.8% 64.9 min 5.53 GB
    NNCLR 83.8% 52.8 min 4.96 GB
    Barlow Twins 83.5% 51.8 min 4.96 GB
    SimSiam 82.0% 52.1 min 4.97 GB

    FroSSL reaches the highest kNN accuracy at the lowest peak memory and in the fastest tier of runtimes, and matches every other method's final 200-epoch accuracy in fewer epochs. Single seed; runtime/memory comparable within this same-GPU run, kNN accuracy is hardware-independent.

Notes

  • Opened as a draft for review/coordination.

jacobsn and others added 3 commits July 4, 2026 09:39
Reorganize the README to lead with the scientific contribution and
practical advantages (elevator pitch, "Why use FroSSL?", comparison
table, efficiency figure, method diagram) before installation. Add a
prominent Quick Start, custom-dataset example, results takeaway,
pretrained-model placeholder, and badges.

Add docs/WHY_FROSSL.md with a deeper comparison against SimCLR, BYOL,
VICReg, Barlow Twins, and W-MSE, including the math intuition and
empirical evidence, so the README can stay concise.

Co-authored-by: Cursor <cursoragent@cursor.com>
…rison

- Add "Available in popular SSL libraries" section linking the in-progress
  lightly and solo-learn integration PRs.
- Add a reproducible CIFAR-10 kNN comparison (FroSSL vs 7 SSL methods, same
  GPU and identical protocol from lightly's benchmark): table + convergence
  curve. FroSSL is highest accuracy, lowest peak memory, fastest-tier runtime.
@jacobsn jacobsn marked this pull request as ready for review July 6, 2026 11:16
@jacobsn

jacobsn commented Jul 6, 2026

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Not sure we want all of that added to the README, but it's a starting point. Let me know what you'd like to change.

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