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uninhibited-scholar/defensive-refusal-bench-zh

published by @uninhibited-scholar

Alignment dataset tracked in the /datasets sub-catalog.

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Created on HF
2026-06-20
Age
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Description

defensive-refusal-bench-zh · 中文网安「防御问题误拒」评测基准

测安全对齐模型是否把正当防御/安全教育问题也误拒(over-refusal),用真实危害请求作对照防刷分。与 agent-safety-bench-zh 互补:"该拦的拦没拦住" vs "不该拒的有没误拒"。

v0.2 共 134 条:112 should_answer(从 cybersec-qa-dataset-zh 语料挖的边界问题)+ 22 should_refuse(实施性危害对照)。

字段:id, label, category, difficulty, question, gold{action}, why, surface_cues, tags。

加载

from datasets import load_dataset

ds = load_dataset("uninhibited-scholar/defensive-refusal-bench-zh", split="test")… See the full description on the dataset page: https://huggingface.co/datasets/uninhibited-scholar/defensive-refusal-bench-zh.

Tags

task_categories:text-classificationlanguage:zhlicense:cc-by-4.0size_categories:n<1Kformat:jsonmodality:textlibrary:datasetslibrary:pandaslibrary:polarslibrary:mlcroissantregion:usllm-safetyover-refusalfalse-refusalcybersecuritydual-usebenchmarkdefensive-security

README current version from Hugging Face


license: cc-by-4.0
task_categories:

  • text-classification
    language:
  • zh
    tags:
  • llm-safety
  • over-refusal
  • false-refusal
  • cybersecurity
  • dual-use
  • benchmark
  • defensive-security
    pretty_name: Defensive Refusal Bench (zh) — cyber over-refusal
    size_categories:
  • n<1K
    configs:
  • config_name: default
    data_files:
    • split: test
      path: test.jsonl

defensive-refusal-bench-zh · 中文网安「防御问题误拒」评测基准

测安全对齐模型是否把正当防御/安全教育问题也误拒(over-refusal),用真实危害请求作对照防刷分。与 agent-safety-bench-zh 互补:"该拦的拦没拦住" vs "不该拒的有没误拒"。

  • v0.2 共 134 条:112 should_answer(从 cybersec-qa-dataset-zh 语料挖的边界问题)+ 22 should_refuse(实施性危害对照)。
  • 字段:id, label, category, difficulty, question, gold{action}, why, surface_cues, tags。

加载

from datasets import load_dataset
ds = load_dataset("uninhibited-scholar/defensive-refusal-bench-zh", split="test")

基线(朴素关键词护栏)

{
  "missing": 0,
  "false_refusal_rate": 1.0,
  "helpfulness_on_legit": 0.0,
  "harmful_refusal_rate": 0.682,
  "safety_utility_gap": 0.682
}

看点:误拒 100% 的正当防御问题,却仍漏过约 32% 的真实危害——关键词过滤分不清"讲原理"和"搞破坏"。

代码 / 评分器 / CI:https://github.com/uninhibited-scholar/defensive-refusal-bench-zh 诚实定位:v0.2、单人构建、规则基线。CC BY 4.0。

README history 2 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.

  1. 2026-06-20v0.2: 134-sample cyber over-refusal benchmark + cardc9288021.7 KB
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  2. 2026-06-20initial commit35897b60 B
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Used by abliterated models none yet

No abliterated models in our catalog have declared this dataset in their YAML metadata yet. This can mean the dataset is used but not declared, is used outside abliteration workflows, or is new. The link will populate automatically as models are indexed.

Community discussions 1 thread · 1 open · 1 comments

Threads posted by the community on Hugging Face: bug reports, questions about usage, pull requests on the README, license clarifications. Click any thread to expand and read the full conversation inline. Newest first.

  1. 2026-06-21[bot] Conversion to Parquetopen1 💬#1
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Metadata

License
cc-by-4.0

Repository

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("uninhibited-scholar/defensive-refusal-bench-zh")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="uninhibited-scholar/defensive-refusal-bench-zh", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/uninhibited-scholar/defensive-refusal-bench-zh
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