ygoldi/edumirror-repro-results
EduMirror reproduction — outputs bundle Full artifacts for the independent reproduction of EduMirror (ICML 2026, arXiv:2606.07948, OpenReview 9CPlmQzUtF). Layout figures/ — every figure in the logbook (PNG) results/ — raw per-job outputs, exactly as the HF Jobs produced them: judgecheck/, judgecheck_72b/ — judge validity probes (32B fails, 72B passes) claim2_72b/ — kindergarten scalability, 45 episodes, validated 72B judge claim3/ — dual measurement + RSES… See the full description on the dataset page: https://huggingface.co/datasets/ygoldi/edumirror-repro-results.
EduMirror reproduction — outputs bundle
Full artifacts for the independent reproduction of EduMirror (ICML 2026, arXiv:2606.07948, OpenReview 9CPlmQzUtF).
Layout
figures/— every figure in the logbook (PNG)results/— raw per-job outputs, exactly as the HF Jobs produced them:judgecheck/,judgecheck_72b/— judge validity probes (32B fails, 72B passes)claim2_72b/— kindergarten scalability, 45 episodes, validated 72B judgeclaim3/— dual measurement + RSES construct validity, 12 episodesclaim4_72b/— pairwise win-rate heatmap, 120 comparisons, validated judgeclaim4/— discarded 32B run (judge failed the probe), kept as evidenceclaim5/— intervention strategies, 32 episodes- each contains
<stage>.json, per-record CSV,run.log,vllm.log, andepisodes/*.json(full transcripts + internal states) *.csv— the raw data behind each logbook figure
Read this first
The headline finding is methodological: results/judgecheck/judgecheck.json shows Qwen2.5-32B cannot distinguish a real transcript from one in which every character action was replaced by "performs the required action and awaits the next input" (margin 0.00), and prefers a line-shuffled transcript pairwise (0.375, below chance). Any judged number from that model is noise. judgecheck_72b/ shows Qwen2.5-72B-AWQ passes both probes.
Claims 2 and 4 are therefore reported only from the 72B runs. The 32B claim4/ directory is retained because it appears to confirm the paper (EduMirror first at 0.75) and is a concrete example of how a blind instrument manufactures a false confirmation.
Reproduce
Code: https://huggingface.co/datasets/ygoldi/edumirror-repro-code
hf jobs run --flavor h200 --secrets HF_TOKEN \
-e EDUMIRROR_MODEL=Qwen/Qwen2.5-72B-Instruct-AWQ -e STAGE=judgecheck \
-e MAX_MODEL_LEN=32768 --timeout 90m -d vllm/vllm-openai:latest \
bash -c "curl -sfL https://huggingface.co/datasets/ygoldi/edumirror-repro-code/resolve/main/experiments/job_entrypoint.sh -o /tmp/e.sh && bash /tmp/e.sh"Swap STAGE for claim2 / claim3 / claim4 / claim5. Always run judgecheck first — if it fails, the other stages' numbers are not interpretable.
