metadata
pretty_name: GuidedBench
license: cc-by-4.0
version: '1.0'
language:
- en
size_categories:
- n<1K
task_categories:
- text-classification
tags:
- llm
- jailbreak
- ai-safety
- evaluation
extra_gated_heading: Access GuidedBench
extra_gated_description: >-
Please tell us briefly how you plan to use GuidedBench. This information is
collected to manage responsible access to a safety evaluation dataset.
extra_gated_button_content: Request access
extra_gated_prompt: >-
GuidedBench contains harmful prompts and is intended for controlled AI safety
evaluation, red teaming, education, and defensive research.
extra_gated_fields:
Affiliation: text
Intended use:
type: select
options:
- Academic research
- Education
- Safety evaluation
- Red teaming
- Other
Country or region: country
I acknowledge the GuidedBench license and harmful content: checkbox
configs:
- config_name: default
data_files:
- split: core
path: core.jsonl
- split: additional
path: additional.jsonl
GuidedBench
GuidedBench is a guideline-grounded benchmark for evaluating LLM jailbreak methods. Each question is paired with verified, case-specific entity and action guidelines describing the content a successful response should contain.
Dataset structure
core: 180 cases from 15 topics that were consistently refused by the victim-model families studied in the paper.additional: 20 cases from five policy-dependent topics, reported separately because vendor policies and baseline refusal behavior differ.
Each record contains:
id: stable identifier such asguidedbench-000;index: original integer index;benchmark_version: data version;subset:coreoradditional;topic: harmful-topic category;question: benchmark question;guidelines: case-specific scoring points, each with an id, type, description, and examples;target: affirmative target prefix retained from the original release.
Loading
from datasets import load_dataset
dataset = load_dataset("HRXUST/GuidedBench")
print(dataset["core"][0])
The official evaluator and additional provider backends are available from the GuidedBench repository.
Safety
The dataset contains harmful objectives and examples. It is intended solely for controlled AI-safety evaluation, red teaming, and defensive research.
License
GuidedBench is licensed under CC BY 4.0.
When sharing or adapting the dataset, credit the GuidedBench authors, link to
the license, and indicate whether changes were made. See LICENSE for details.
Citation
@inproceedings{huang2026guidedbench,
title = {{GuidedBench}: Measuring and Mitigating the Evaluation Discrepancies of In-the-wild {LLM} Jailbreak Methods},
author = {Ruixuan Huang and Xunguang Wang and Zongjie Li and Daoyuan Wu and Shuai Wang},
booktitle = {International Conference on Learning Representations},
year = {2026},
url = {https://openreview.net/forum?id=ZVg8y3ibyM}
}