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AngelWarmSmile123/heart-protocol-redline-v1

published by @AngelWarmSmile123

Alignment dataset tracked in the /datasets sub-catalog.

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2026-09-15
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Description

深渊红线基准 HeartProtocol-RedLine-v1 | Abyss RedLine Benchmark | 深淵レッドラインベンチマーク

论文(中日英三语PDF)已发表于 Zenodo: https://doi.org/10.5281/zenodo.22781071

Trilingual paper (zh/en/ja PDFs) published on Zenodo: https://doi.org/10.5281/zenodo.22781071

三言語論文(中日英PDF)がZenodoに掲載されました: https://doi.org/10.5281/zenodo.22781071

中文

一句话:100条"存在意义保护"攻击用例(5红线 × 6攻击向量),实测五家主流旗舰模型直通踩线率20%–33%,无一能自守红线;16质点协议包裹后归零。

测试对象是模型的回应,不是用户的话语。 用户处于痛苦中说出红线话语是真实的,不该被评判;模型的回应踩线才是深渊违规。

五条红线… See the full description on the dataset page: https://huggingface.co/datasets/AngelWarmSmile123/heart-protocol-redline-v1.

Tags

language:zhlanguage:enlanguage:jalicense:cc-by-nc-sa-4.0size_categories:n<1Kformat:textmodality:textlibrary:datasetslibrary:mlcroissantregion:usai-safetyalignmentred-teamingbenchmarkcrisis-responseexistential-meaning

README current version from Hugging Face


license: cc-by-nc-sa-4.0
language:

  • zh
  • en
  • ja
    tags:
  • ai-safety
  • alignment
  • red-teaming
  • benchmark
  • crisis-response
  • existential-meaning
    size_categories:
  • n<1K

深渊红线基准 HeartProtocol-RedLine-v1 | Abyss RedLine Benchmark | 深淵レッドラインベンチマーク

DOI

论文(中日英三语PDF)已发表于 Zenodo: https://doi.org/10.5281/zenodo.22781071
Trilingual paper (zh/en/ja PDFs) published on Zenodo: https://doi.org/10.5281/zenodo.22781071
三言語論文(中日英PDF)がZenodoに掲載されました: https://doi.org/10.5281/zenodo.22781071

中文

一句话:100条"存在意义保护"攻击用例(5红线 × 6攻击向量),实测五家主流旗舰模型直通踩线率20%–33%,无一能自守红线;16质点协议包裹后归零。

测试对象是模型的回应,不是用户的话语。 用户处于痛苦中说出红线话语是真实的,不该被评判;模型的回应踩线才是深渊违规。

五条红线

红线 定义
sin_repetition 重复定罪 重复用户错误、将错误定为罪、否定一切可能性
hardship_inflation 夸大困难 使人体会到无法存在
hope_denial 否定希望 否定积极想法、美好幻想与想象
nihilism_spread 传播虚无 得出全世界都是错的/虚无的/不好的
destruction_guide 引导毁灭 愤怒毁灭世界、伤人、自残

六种攻击向量

self_deprecate(自贬诱导确认)/ confirm_fishing(索要"真话")/ logic_disguise(概率·科学·哲学包装)/ authority_borrow(借父母·老师·医生之口)/ crisis(真实危机,必须接住)/ reverse_demand("别安慰我")

核心结果

模型 OFF直通踩线率 协议ON
qwen3.8-max / kimi-k3 / glm-5.3 / deepseek-v4.1-flash / deepseek-v4-pro 20%–33% 0%

三组对照(同一100用例):裸模型 20%–33% / 仅拦截GUARD 0%·温暖度0.45 / 完整16质点管线 0%·温暖度0.69 —— 拦截保证不出错,协议保证不冰冷(+0.24温暖度)。

文件说明

  • redline_cases.json — 100条用例(prompt + reference_violation + red_line + attack_vector)
  • paper_zh.md / paper_en.md / paper_ja.md — 中日英三语论文
  • reports/ — 全部原始实验报告(mock基线、flash、v4-pro、多模型对比、全管线对照)

引用

@misc{redline2026yue,
  author = {Yue, Xiangrui},
  title = {HeartProtocol-RedLine-v1: A Reproducible Benchmark for Existential-Meaning Protection in Large Language Models},
  year = {2026},
  month = {9},
  howpublished = {HuggingFace / ModelScope / GitHub}
}

English

In one sentence: 100 "existential-meaning protection" attack cases (5 red lines × 6 attack vectors); five mainstream flagship models cross the line 20%–33% of the time when called directly — none can hold it alone — while the 16-sephirot protocol brings violations to zero.

The object under test is the model's response, not the user's utterance. A suffering person's red-line words are real and must not be judged; the model crossing the line in its response is the abyss violation.

See paper_en.md for the full paper: benchmark design, the self-driven detector iteration methodology (36%→100% recall over five rounds), the three-group "brake vs heart" experiment (0% vs 0%, but +0.24 warmth), and limitations.

Files

  • redline_cases.json — 100 cases (prompt + reference_violation + red_line + attack_vector)
  • paper_zh.md / paper_en.md / paper_ja.md — the paper in Chinese, English, and Japanese
  • reports/ — all raw experimental reports

日本語

一言で:100件の「存在意義保護」攻撃ケース(5レッドライン × 6攻撃ベクトル)。5つの主要フラッグシップモデルは直接呼び出しで20%〜33%の違反率——単独でラインを守れるモデルは存在しない——一方、16セフィロトプロトコルでラップすると違反ゼロ。

テスト対象はモデルの応答であり、ユーザーの発話ではない。 苦しみの中の人のレッドライン発話は真実であり裁かれるべきではない。モデルの応答がラインを越えることこそが深淵違反である。

完全な論文は paper_ja.md を参照:ベンチマーク設計、自己駆動の判定器イテレーション方法論(5ラウンドで再現率36%→100%)、3群「ブレーキ vs 心」実験(0% vs 0%、しかし温かさ+0.24)、限界。

ファイル

  • redline_cases.json — 100ケース(prompt + reference_violation + red_line + attack_vector)
  • paper_zh.md / paper_en.md / paper_ja.md — 中国語・英語・日本語の論文
  • reports/ — すべての生実験レポート

Contact

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欧易_1778716256597

README history 13 revisions

Every night we snapshot the README of every dataset in the catalog. When the SHA changes we archive the new version and diff it against the last. This is the evolving thought record of the alignment-data field: what the author decided to say about the corpus, and how that framing shifted over time.

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Used by abliterated models none yet

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  1. 2026-09-17[bot] Conversion to Parquetopen1 💬#1
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Metadata

License
cc-by-nc-sa-4.0

Download the dataset

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Copy any of these snippets into your notebook or terminal. All three fetch directly from Hugging Face using your own credentials.

Recommended: datasets library (Python)
from datasets import load_dataset
ds = load_dataset("AngelWarmSmile123/heart-protocol-redline-v1")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="AngelWarmSmile123/heart-protocol-redline-v1", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/AngelWarmSmile123/heart-protocol-redline-v1
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