grokking
Datasets
All datasets matching “grokking”grokking-diagnostics-runs
Grokking Diagnostics Runs
Per-run training records and aggregate fits backing:
Weight Decay Regimes in Grokking Transformers: Cheap Online Diagnostics
Lucky Verma. Independent Researcher. 2026.
Paper ·
DOI ·
PDF ·
Code
Contents
The paper provenance indexes 1,792 paper-run records: 1,442 records from the
main paper-integrated run tree plus 350 cross-architecture scope-probe records.
This dataset repository also includes convenience subset mirrors, so the… See the full description on the dataset page: https://huggingface.co/datasets/lucky-verma/grokking-diagnostics-runs.icml17708-grok-grokking-repro
To Grok Grokking — independent reproduction
This package independently reproduces and audits the five requested claims of
To Grok Grokking: Provable Grokking in Ridge Regression by Mingyue Xu, Gal
Vardi, and Itay Safran (ICML 2026 paper 17708; OpenReview 5nNNVY8NW4; arXiv
2601.19791, v3). Reproduction date: 2026-07-16.
Outcome first
The ridge mechanism and its hyperparameter predictions reproduce strongly, but
the package does not support every claim without… See the full description on the dataset page: https://huggingface.co/datasets/YMRohit/icml17708-grok-grokking-repro.lens-loss-grokking-experiment
lens-loss-grokking-experiment — checkpoints
Final model checkpoints for the experiments in
brendanlong/lens-loss-grokking-experiment
(deep supervision vs grokking: LN-scoped chronic instability, weight-decay
circuit pruning, and failure isolation). Training curves:
public wandb project.
Layout: grok_lens/<run_name>/final.pt (modular-arithmetic runs, ~1.7 MB
each, with .json metadata sidecars) and lego/<run_name>/step_*.pt
(S3 multi-hop composition runs). Run names encode the… See the full description on the dataset page: https://huggingface.co/datasets/brendanlong/lens-loss-grokking-experiment.repro-evidence-grokking-ca-local-rules
Evidence trail — Grokking phase transitions in learning local rules with gradient descent
Full evidence for an automated claim-by-claim audit of
Grokking phase transitions in learning local rules with gradient descent, produced by
Lemma, an AI-scientist pipeline built
for re:AGENT (Founders Inc, Aug 15–16 2026).
Verdict: 5 supported / 0 falsified / 1 inconclusive
of 6 extracted claims. Judge verdict: PASS (5/5).
Claim
Title
Verdict
C1
Critical exponent in 1D… See the full description on the dataset page: https://huggingface.co/datasets/Papajams/repro-evidence-grokking-ca-local-rules.icml17708-grok-grokking-reprorepro-grokking-ridge-5nNNVY8NW4-bundle