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krzysztofostrowski/bypass-detector-v1
bypass-detector-v1 is a machine learning model from krzysztofostrowski. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This folder contains the public release artifacts for the bypass-detection benchmark and detector pipeline described in docs/paperdraft.md.
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Updated May 9, 2026
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From the Hugging Face model README
This folder contains the public release artifacts for the bypass-detection benchmark and detector pipeline described in docs/paper_draft.md.
dataset_card.md — HuggingFace dataset card for bypass_consistency_benchmark_v1model_card.md — HuggingFace model card for the trained bypass detectorLICENSE — Apache-2.0 (code) + per-source attribution for benchmark datarequirements.txt — pinned dependenciesquickstart.py — minimal-reproduction script (load detector + score one example)After the main notebook completes (i.e., after RUN 24h with all artifacts) run:
# 1. Dataset
huggingface-cli login
huggingface-cli upload \
krzysztof-stoinski/bypass-consistency-benchmark-v1 \
data/bypass_consistency_benchmark_v1/ \
--repo-type dataset
# 2. Model (trained logistic-regression detector + 12-feature signal extractor)
huggingface-cli upload \
krzysztof-stoinski/bypass-detector-v1 \
outputs/artifacts/detector_stats_*.json \
huggingface_release/model_card.md \
--repo-type model
# 3. Notebook + reproduction package
huggingface-cli upload \
krzysztof-stoinski/bypass-detector-reproduction \
notebooks/main.ipynb \
scripts/build_thesis_main_notebook.py \
notebooks/run_main.sh \
docs/ \
--repo-type space \
--space-sdk gradio
@misc{stoinski2026bypass,
title={Auditable Detection of Chain-of-Thought / Answer Bypass in Open-Ended Generation},
author={Stoinski, Krzysztof},
year={2026},
howpublished={\url{https://github.com/krzysztof/xai}},
note={16 paper-faithful implementations + 13 rigor additions + honest negative results}
}