schema string | mode string | list string | list_sha256 string | reuse string | t07_record_sha256 string | bootstrap dict | rules dict | n int64 | sets list | rows list | llm_minus_ft list | readings dict | reproduces_t07 dict |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
wrsi.t07_v5_table.v1 | dev | scripts/sealed/finals_v5.json | 6a6e572c392cdd508dc7af2be817f52ac7075ecf163ae3ddc6b8a32428f81b55 | scripts/sealed/finals_v5_reused.json | 55982f0da04b35140b494022768e64e4f0aa2115f7aff4084fbd2453265fa556 | {
"seed": 20261107,
"generator": "numpy default_rng",
"n_resamples": 1000,
"n_images": 4000,
"interval": "percentile 2.5 and 97.5 (numpy linear)"
} | {
"help": ">= +1.0 point and CI above 0",
"harm": "<= -1.0 and CI below 0",
"recovered_share": "change / (base clean acc - base set acc), loss >= 2.0"
} | 4,000 | [
"clean",
"gaussian_noise_s1",
"gaussian_noise_s2",
"gaussian_noise_s3",
"gaussian_noise_s4",
"gaussian_noise_s5",
"contrast_s1",
"contrast_s2",
"contrast_s3",
"contrast_s4",
"contrast_s5",
"defocus_blur_s5",
"snow_s5",
"shot_noise_s5",
"impulse_noise_s5",
"motion_blur_s5",
"zoom_blur... | [
{
"arch": "vit",
"network": "llm_gaussian_noise",
"set": "clean",
"group": "clean",
"severity": null,
"delta_points": 0.125,
"ci95": [
-0.1,
0.35000000000000003
],
"boot_sd": 0.11707007688945499,
"label": "neutral",
"fixed": 13,
"broken": 8,
"worst_cla... | [
{
"arch": "vit",
"condition": "gaussian_noise",
"set": "clean",
"group": "clean",
"n": 4000,
"llm_minus_ft_points": 0.7500000000000062,
"ci95": null,
"paired": false,
"note": "point only: a counts-only earlier record has no per-image correctness"
},
{
"arch": "vit",
"... | {
"vit llm_gaussian_noise": {
"help_sets": [
"gaussian_noise_s1",
"gaussian_noise_s2",
"gaussian_noise_s3",
"gaussian_noise_s4",
"gaussian_noise_s5",
"shot_noise_s5",
"impulse_noise_s5",
"frost_s5",
"speckle_noise_s5"
],
"harm_sets": [],
"n_sets": ... | {
"equal": true,
"differences": []
} |
WeightCode: records and weights
Experiment records and trained weights that accompany the WeightCode code release (github.com/Gen-Verse/WeightCode). The code repository is small and holds no data. This dataset holds what a reader needs to audit the reported numbers and to rerun the learned programs.
Layout
| Path | What it holds |
|---|---|
records/sessions/<id>/ |
Text records of 88 LLM sessions: task, prompts, tool calls, transcript, attempts, patches, final/ program and selection, audit and result files |
records/sealed/ |
Numbers of record from the sealed reads: registry.jsonl, manifests/, results/ (per-entry metrics and hashes, no test pixels) |
records/tables/ |
Reference-stream, sealed-read, T07 and mechanism tables copied from the run store |
records/finals/ |
The frozen finals lists, finals_v1.json to finals_v6_secondary.json (also in the GitHub repo) |
weights/instances/<id>/ |
The 23 networks and instance specifications that the finals lists refer to (model.npz, evidence.npz, model_spec.json, forward.py, task.json) |
weights/session_finals/<id>/ |
Final parameter deltas and edited models of the 21 sessions that the finals lists refer to |
MANIFEST.json |
Session origins, original directory of every instance, list of exclusions |
SHA256SUMS |
Checksum of every file except this card |
REDACTIONS.json |
The files in which two account identifiers were replaced, and what was replaced |
Session ids and instance ids are the ones used in the finals lists. child_sha256 in a finals entry identifies the
program that was evaluated.
Using it
This is not a drop-in experiment store. The code expects $WEIGHTCODE_RUNS/sessions/<id> and
$WEIGHTCODE_PRIVATE/instances/<id>. To rebuild that layout, link records/sessions and weights/instances to those
paths. Instances that were originally kept in other private subdirectories (for example scan_instances and
e14_instances) are all under weights/instances here, and MANIFEST.json gives their original location.
from huggingface_hub import snapshot_download
snapshot_download("Boom5426/WeightCode", repo_type="dataset", local_dir="weightcode_data")
Verify a download with sha256sum -c SHA256SUMS from the dataset root.
Redaction
On 2026-11-10 two identifiers of the authors' compute accounts were replaced in the text records: a personal login
name (now <redacted-account>) and a cluster project number (now <redacted-project>). REDACTIONS.json lists the
files and the number of replacements in each. Nothing else in those files changed: every number, hash, program and
weight is as recorded. A record that quotes the sha256 of one of these files quotes it as it was before the redaction,
so that quote no longer matches. SHA256SUMS gives the hashes of the files as published here.
Not included
- Fixed-reference and fine-tuning trajectories (
.npy, about 48 GB). They are regenerated by the scripts in the code repository. - Qwen3 base weights, which are public from their original model pages.
- Public datasets (CIFAR-10, CIFAR-10-C, ImageNet and others) and sealed test pixels. The code repository contains the build scripts.
- Session working directories (
private/,scratch/,cwd/) and arrays outsidefinal/.
License
MIT, the same as the code.
- Downloads last month
- -